游戏邦在:
杂志专栏:
gamerboom.com订阅到鲜果订阅到抓虾google reader订阅到有道订阅到QQ邮箱订阅到帮看

万字长文,能为玩家游戏心理设计锦上添花的奖励设定探讨,上篇

发布时间:2015-11-17 09:45:21 Tags:,,

篇目1,关于奖励机制在游戏中的运用思考

当游戏开始游戏化的时候

游戏化通常被用于非游戏领域以互动奖励的方式完成对用户粘着度的权衡途径,但事实上当我们回归视角仔细审阅轻游戏(比如以休闲为宗旨的Casucal游戏)的时候更能够发现游戏化运用最为娴熟的仍然在游戏领域,而游戏性外的刺激性奖励元素正在被强势挖掘以致成为能够影响游戏价值举足轻重的环节。

特别是社交游戏和网页游戏(包括PC端和Mobile端)对游戏化的演绎更为极致,几乎对应的是玩家的每一个点击和操作行为,包括部分累积行为(比如量化累积后)都能够轻易导向资源型、经验型、道具型和勋章型的收集和获取,以分属性和分批量供应的方式不断给以玩家在获得层面上丰盈的错觉,尽管事实上这些不断供应的奖励在量级和属性表现上可能独立开来并不算有明显的效能,甚至基本上不会在游戏表现中起到什么积极性的效用,但以次数和获得几率的双重强化让玩家的累计丰收感时刻十足。

当然同样存在缺失节制的过度化趋势,最为典型的是在基本没什么游戏操作行为的情况下快速升级,并进入快速接任务,快速完成任务,快速获取奖励的定式循环,以纯粹点击鼠标的方式和额外奖励(包括属性获得)的刺激因素不断驱动玩家在快节奏中不断前进(诸如部分网页游戏的寻径一般是自动的,而很多副本行为是过场动画完成的,玩家只需要在指示中点击按钮升级就能获得额外满满的成就),于是游戏开始衍化为游戏化的选项,从行为-进程装扮为行为-奖励,这在社交游戏中发挥得同样淋漓尽致(依靠外部奖励推动让游戏看起来似乎有趣,并且让这种收获感便成为日常行为)。

关于奖励激发效能的分析

如果仔细探究各种不同类型游戏的话,不管是Hardcore、Midcore或者Casual类型的游戏都基本存在着对玩家资源性层面累积值的因素,我们在上一期关于游戏模式化的文章中曾提到最核心的一种就是资源进阶模式,这涉及到玩家的资源累加、装备强化和玩家级别经验的提升,当时提到该类游戏的进阶乐趣更多在于宽泛资源的捕获/收集/奖励(可支配货币系统、锻造强化系统、装扮系统亦或者超级战力)和由此带来的成就满足(强战力或者强装扮力所带来的比照心理满足)。这几乎就是大量游戏的固定套路,大部分的指向都是资源、经验和金钱性的增长奖励,或者依靠玩家的自我累加以达到解锁全新关卡的能力,诸如FPS游戏中的Contract Killer(任务-终结目标-累积资源-新战力-新任务),城建游戏Cityville(建造-等待-收益-更高阶的建造),其中所伴随的便是现有的激励以及新阶段的激励预期让玩家在进程中呈现了某种被预设的成就性,而表象便是如在Quake中劫杀怪物让玩家自我感觉异常强大,而Civilization则让玩家释放了征服的帝国欲望,换句话说游戏整体由部分累加而成的各个环节的促动最终汇聚了玩家对游戏该有的倾向性理解,这也是我们在游戏中常自我认为的游戏整体奖励,从小的环节中累积并在最后完成对玩家的终极释放。

有些分析师甚至试图去解构玩家在奖励层面上之于获得的心理满足感,但看起来原本不属于玩家只是随着游戏的点击进程以额外奖励的方式赋以玩家的资源、经验和勋章表彰即使在游戏方案中是预先设定完好的,但对玩家也是一种增值获得,并且大半的奖励都是区分种类、立体呈现还能够很直观地由玩家带着欢愉的声效收入背包,这种只需要轻易点击不需要真实消费所获得的成分在任何时刻对于玩家而言格外满足(相比较于在这个环节上不设置奖励,此时的收获就有可能从寻常甚至微不足道中看出一点珍贵来,尽管从游戏研发的层面看奖励的设定可多可少,同样特定份额的奖励可以一次获得也可以拆分为不同的礼包由玩家在执行不同的任务中各自获得,这点在玩家的感受上因为进程节奏和点击频度快往往是很容易忽略的。此时,在不影响玩家进程的基础上奖励看起来更像是一种仪式,玩家所得便是一种名分和往后从背包中查阅和使用资源的愉悦)。

Angry-Birds-Rio-Golden-Beachball(from angrybirdsnest.com)

Angry-Birds-Rio-Golden-Beachball(from angrybirdsnest.com)

当然从Free To Play游戏模式的角度,甚至这些奖励所得在商城消费的比照下瞬间就显得黯然失色,但这并不妨碍游戏进程设定的奖励在当刻对玩家的心理触动,这些奖励是实在的归于玩家个人所有的获得,级别获得了提升,金钱数字获得了增长而一无所有的背包也开始慢慢充盈起来,更关键的是玩家只是点击了鼠标便轻易获得了为数可观的奖励,在没有比照的环境下,这种获得的满足感会被情绪刻意放大,即便奖励的次数多到数不过来和每次给以的量都无法产生实质性的效能,玩家的心态最不济也是欢迎的,只有在遭遇消费型玩家所获得的超级战力所可以比照出来的差异化中玩家才会被拉回残酷的现实,之前再多的奖励终究是抵不过一次道具消费的。

回到我们刚才提到的奖励正面效能,除了每次领取时可能的短暂满足愉悦,奖励的设定同样因为部分服务于游戏进程(游戏邦注:诸如城建游戏中有更多的金钱去建造更具价值性建筑;角色扮演游戏中有更好的技能去和NPC或者现实玩家进行战力格斗)让玩家的升级更为流畅而获得认可,特别是当奖励的设定刚好和玩家当时的需求相衔接时(比如游戏任务要求锻造某项装备而奖励刚好带来了该需求最被需要的零配件),甚至能够带动出玩家的些许感激来(满足玩家对奖励的预期,或者超越于玩家的预期,而不是只是提供可有可无的资源,特别是这些资源看起来没有太多合适用途的时候)。

当然除了实用性的层面,在游戏场景中被众多玩家提及,并且看起来供应量有限的奖励也能够将这种满足感提升到更高的级别(诸如羊羊家园中玩家所津津乐道的电力灰太狼BOSS任务和奖励对未达到级别的玩家完成了一次超前的美好憧憬,而当实质执行任务时,期盼已久的奖励如期而至这种玩家印象甚至能更为深刻)。

关于奖励本身的分析

一般情况下游戏的奖励方式可分为五个部分:

其一是完成任务或进程的奖励(完成游戏任务环节或玩家游戏关卡都伴随着特定资源的奖励,前者诸如Contract Killer完成暗杀任务,后者诸如Parking Mania完成停车关卡获得金币奖励,这部分可以用来购买剩余的游戏关卡);

Angry-Birds-Rio-Bonus(from angrybirdsnest.com)

Angry-Birds-Rio-Bonus(from angrybirdsnest.com)

其二是游戏进程中的收集(这部分包括两个环节:第一个是设定隐藏的奖励,诸如Batman: Arkham Asylum中到处潜藏着可以收集的战利品,这种类型的奖励能够满足玩家的收集喜好更能够增加游戏的探索属性以及延长游戏的生命周期;第二个是与其他的NPC对抗获得的奖励,诸如Blade Of Darkness与鬼魅对抗获得的生命值,羊羊家园中与狼族对抗获得道具配方、卡片碎片或者在穿越三国中某项特殊技能的解锁获得);

其三是登录奖励(一般也分为两个层面:第一个是每日登录奖励,这个更多体现在社交游戏中以激励玩家定时返回游戏中,诸如City of Wonder的奖励设定;第二个是连续登录奖励,这个主要是对不间断登录用户提供的阶梯式奖励,诸如德州扑克就以一周为循环时间点,以7天为限对不间断登录的用户进行游戏币奖励);

其四是成就展示比照奖励(即便是单机型游戏也往往借助第三方的排行榜系统向不同的玩家做成就展示,最典型的就是App Store的Game Center,而游戏设计师Lucas Blair还专门针对游戏成就因素对玩家的激励效能做过分析,Lucas Blair在分析中认为激励玩家自我极限挑战以获得成就和给以玩家预想不到的成就奖励能够更好地提升玩家对游戏项目本身的沉浸性。因此在成就奖励层面,呈现更多的往往是精神层面的满足感,诸如玩Angry Birds某个关卡从1颗星通过晋升到3颗星通过,当然这种模式也存在着弊端,一旦玩家以3颗星的实力通过该关卡,基本上玩家就很难再有可能回到该关卡重复体验了;诸如在篮球传奇中以绝对领先的比分击败PK对手,竞技成分所隐藏了最大推动力就是驱动玩家在竞技的背后不断优化自己的相关属性以期待在竞技场能够一举击败对手);

其五是从虚拟延伸到现实环境的奖励(这个存在多种模式:第一个是以Kiip为表征的将游戏与实物奖励进行了捆绑,玩家只要完成相应的任务就能获得对应的实物兑现;第二个是以Foursquare为表征的将LBS签到和商用环境进行了捆绑;第三个则更为直接体现为广告游戏,或者直接为实体提供介绍或者将优惠码接入其中,诸如Belly & Brain或者Burger King)

关于奖励中的必现和概率问题

事实上,因为政策限制,特别是涉及到用户需要投入真实钱币情况下的奖励概率基本上是被限定的,诸如在日本的kompu gacha已经被明令要求指明玩家在投入钱币后所能够得到的概率,以防止用户在暗箱中被损失,而国内曾风行一时的开宝箱玩概率的时代也同样需要面对政策的限制。

而在非真实钱币投入的情况下部分游戏在完成任务或者关卡结束时仍然为游戏提供了概率选项,诸如疯狂宠物中玩家在完成天梯战役后不管输赢都有一次机会站在轮盘前刷一次命运奖励,而这就涉及到了轮盘奖项的概率问题(游戏邦注:非真实钱币投入,只涉及玩家在不需要投入的情况下获得的奖励的大小)。

这个环节上就存在设定的比例因素,诸如A为超小概率,B为小概率,C为中概率,D为大概率,在疯狂宠物的轮转盘上或者在捕鱼达人的捕鱼场景中,概率的设定就影响了玩家在本次投入获得的回报率,并且在不出现累积的情况下,玩家每一次选择都是相同的概率,基本不会出现A概率前面一直没有爆出后面可能会集中出现的情况,也不会出现10次选择出现3次A概率就认为A概率被累积提升的状况,但所有的因素都会无限制刺激玩家在选择中的态度,患得患失以致出现赌徒心态,认定下一次就有可能找回好的运气。

这个就是我们必须要分析的概率和不均衡选项对玩家心理的牵制:赌徒心态,其一是让奖励形态更戏剧化;其二是刺激用户不间断地回到奖励场景中来。游戏设计师Chris Birke和心理学家B.F. Skinner在研究玩家的游戏表现后都认为具有变量因素的随机概率对玩家在不想错过什么的心态中频繁回到游戏更为有利(如果是固定的,并且这个奖励的吸引力不足够大的话,对用户该有的牵制力就相应地小很多)。

篇目2,分析游戏奖励的需求层次及其用法

作者:Chelsey Webster

引子

奖励是一切游戏中的重要特征,因此是可见于所有游戏类型的元素。奖励的形式和大小多种多样,如果奖励得当,就能够极大增加玩家的游戏乐趣,激励他们继续玩游戏。

奖励甚至可以让玩家去做一些他们原本并不想做,或者不喜欢做的事情。许多玩家仍然会为了奖励而做一些无趣枯燥的事情。这种让玩家去做违背自己意愿的事情足以证明奖励的威力。它们是设计师的重要工具。

设计奖励结构

奖励不应该只是心血来潮的产物,而应该富有结构和计划。以下图表就是根据马斯洛需求层次而调整的奖励结构。

heirarchy_what_goes_where(from gamecareerguide)

heirarchy_what_goes_where(from gamecareerguide)

从上图可看出,每个环节都是上一层的基础,而上一层又总比下一层更强大。如果有某个环节缺失了,上一层次也就不复存在。所以在设计奖励结构时,应该从最底层开始自下而上地动工,以便得到稳定的结构。这也是每个层次需要环环相扣的原因所在。越高级的层次,其奖励频率就要越大。这里应该采用碎片模式(游戏邦注:例如,10个小奖励=1个大奖励,10个大奖励=1个核心奖励)。当然这并不需要严格的碎片化,但小奖励的数量要超过大奖励,以此类推。

我们越往上层走,其奖励就会更趋于有形。最底层的奖励对玩家来说最基础和内在性——玩家体验。而在这个金字塔顶端的奖励,则完全是装饰性的,并且无法脱离底层奖励而存在,尽管它能够强化底层的奖励。我们可以用一杆步枪的射程为例,如果它射程大,那么这杆枪就很棒,但前提是要有这杆枪才行。

我们将在下文中介绍每个层次及其奖励的内容。此处所举例子常见于冒险或RPG游戏,但其原则适用于任何游戏题材。奖励结果应该根据自下而上的重要性进行设计。

奖励玩家体验

在考虑其他细节之前,一定要先完善玩家体验。优秀玩法和沉浸感一定要贯穿游戏机制、美术设计和UI(包括关键的玩家反馈)。我们很难定义这个环节是否已经实现,因为趣味属于只可意会不可言传的东西。一定要让玩家享受在游戏中逗留的乐趣。《侠盗猎车手》(GTA)系列在这方面就表现良好——游戏中没有设定目标,也没有奖励(事实上玩家还会因为丢失弹药和支付医药费而受到惩罚),但人们还是乐此不疲,因为其游戏玩法/机制本身就已经如此有趣和具有内在奖励性。极少有游戏的趣味能够到达这种境界——让人们不祈求任何奖励而自愿玩游戏。也许这正是GTA如此成功的原因。

核心和长期奖励

完善玩家体验之后,就要考虑其核心/长期奖励。这是玩家所获得的最大奖励。这方面的例子包括主要情节开发、开启新内容的主要里程碑(例如在GTA中进入一个新岛屿),或者获得一个新游戏机制,例如《Crash Bandicoot 3》每一场boss战后出现的机制。由于这些是玩家所得到的最大有形奖励,并将影响其内在体验,因此只能让它们偶尔出现。这可以保证它们的价值,避免干扰玩家。如果人们每隔10分钟就能得到一项新技能,他们迟早会抓狂的,因为他们根本来不及学习新技能。

主要和中期奖励

这可以是升级、完成任务、获得大量XP或金钱等。这些奖励对当时的玩家来说很重要,但并不是可以永久保存的奖励。它们本身就极具奖励性,但也意味着它们会走向终结,并最终被他物替代或者变得多余。

短期和次要奖励

这些小型、频繁的奖励本身并不会给玩家带来多大好处,但可以整合成一个大奖励。这方面的例子包括搜集某项道具,小数额的金钱/XP以打败敌人,或者完成某个任务中的一个环节。主要奖励意味着更大的终结,次要奖励则意味着小规模的终点(即走向主要/中期奖励)。

装饰性奖励

这是最后考虑的一个环节。在这个阶级的最高层,它们只有纯装饰性功能,只能作为玩家进程的一个视觉测量指标。在某些情况下,它们只有信息量,例如显示在屏幕上的得分数据,在《质量效应》中的小队选择屏幕。

另一方面,揭开地图或填充进度条等视觉进程元素可以积极鼓励玩家去做原本可能不会去做的事情。玩家可能会因为看到自己的经验条接近于升级水平时,就会再多玩10分钟的游戏。如果不是看到成就挑战,他们可能不会试图以1颗手榴弹放倒10个敌人来挽回局面;如果没揭开地图,他们可能就不会跑遍整个区域。

虽然移除这些装饰性奖励后,游戏可能仍然具有趣味,但它们却可以增强玩家体验,因为玩家可以从中看到自己的表现情况。视觉奖励有助于玩家猜测和预期所得的回报,这是一个不容忽视的激励因素。视觉奖励从来不会真正影响进程或游戏的其他任何层面。

玩家反馈(它出现于最底层次)与装饰性奖励(位于最顶端)之间的界线模糊。玩家反馈是用户沟通交流的关键,但装饰性奖励则可独立存在,或者融入玩家反馈丰富视觉效果。这两者的一个明显区别在于,忽略玩家反馈可能会破坏游戏,或者至少打破沉浸感。例如,看到你的虚拟角色在游戏世界中移动时,如果它只是简单地飘浮在地表上,这就会彻底打破沉浸感,让许多玩家大失兴趣。《湮灭》和《辐射3》中都曾出现类似问题。其中的虚拟角色确实会移动,但沿对角线奔跑时的方向与动作却并不一致,所以角色看起来像是浮在地面上。在玩第三人称游戏时,这种情况会彻底破坏沉浸感。

虽然我们是自下而上设计奖励层次,但玩家通常是自上而下体验这种结构。他们会先看到装饰性元素和次要奖励,例如获得一个任务(这是他们原本就有的奖励),之后就是收集道具和XP这种次要奖励,这会引向一个更大的奖励(通过完成任务或升级而获得),最后是得到新机制或解琐新世界等核心奖励。

成功游戏的例子

这个层级包括《魔兽世界》中的奖励。

heirarchy_wow(from gamecareerguide)

heirarchy_wow(from gamecareerguide)

以上仅选取游戏中的部分奖励内容,但很显然这款游戏每个关卡的奖励都很丰富。其游戏世界和玩法极富沉浸感,玩家体验(职业、专长、PVP/PVE、RP等)的定制化程度也如此之高,这意味着它一款游戏就结合了成百上千种玩家体验。

各类无限量供应的奖励都会相互关联,并集合起来引向更大的奖励。而在其最顶端却是一个装饰性的随机奖励。即使是最无趣的怪兽也可能随机而罕见地掉落特大奖励。玩家在游戏中总能找到继续玩下去的理由,从各方面来看这都是一个极为强大的奖励结构。

失败游戏的案例

我曾为了自己的论文而制作了一款非常简单的2D太空射击游戏。虽然它很适合作为试验品并且能够得出相应结论,但其游戏本身在现实世界中却并不受欢迎。在开发了这种奖励结构后,我决定将其运用于我的游戏:

dis_game_heirarchy(from gamecareerguide)

dis_game_heirarchy(from gamecareerguide)

游戏的顶端很强大,但越往下走越脆弱。这种游戏在今天的市场上毫无立足之地,无论其顶端结构究竟有多好,因为其底层结构并不完整。由于游戏玩法缺乏生气,这整个环节都丢失了。紧凑的时间和有限的资源意味着游戏需关注可以快速而轻易创造的有形奖励。因为我没有时间去创造出色的玩法,这款游戏仅仅是可以运行而已。

我们很容易将这款游戏与70年代的流行街机游戏进行对比。后者在当时很成功,尽管它们包含出现于积分排行榜前列的长期奖励——但它们的主要吸引力却在于怀旧风格。当今的游戏拥有更为复杂的玩法和奖励结构,所以这样一款游戏根本就没有竞争力。

让我们看看,如果《魔兽世界》丢失了一个层次会怎样:

heirarchy_section_removal(from gamecareerguide)

heirarchy_section_removal(from gamecareerguide)

从上图可知,去掉这个层次后,整个层级不再可行。例如,升级增量没了,玩家就得用刷任务的方法从第1级升至90级。玩家会一直很弱,并在紊乱的一段时间后突然变得无比强大。他们需要999亿点XP才能升到下一级,在玩家每击败一个敌人只能获得20点XP的情况下,这种目标真令人沮丧。

移除这个层次完全削弱了下层奖励的价值。次要和视觉奖励对下一轮目标的作用甚至小,所以根本感觉不出其中的奖励性。玩家感到自己的目标是确实何行之时才会更乐意玩游戏。

总结

质量并不等于数量,但每个层次至少要有一个奖励。要满足每个层次的奖励,确保它们集合成另一个更大的奖励。虽然这个结构还没有进行大规模试验,但遵循这种做法却可以让你的游戏实现强大、结构分明、有益的玩家体验。

在设计奖励结构时运用这一模型,可以确保游戏拥有扎实的根基,并且令玩家获得良好的感觉,从而让他们持续在游戏中逗留。

篇目3,举例分析游戏奖励的心理学原理

作者:Max Seidman

在过去2年里,我有幸在Tiltfactor与Geoff Kaufman博士一起工作,他是社交心理学领域的哲学博士,也是我们的实验室研究的的领导者。除了具有一些独到的见解外,他也对我们所开发的一些游戏进行了正式的研究,我也学到了许多有关心理学的内容,并形成了许多有关它是如何影响游戏的理论,同时还列出了游戏设计师们必须牢记的一些要点。最近我投入了大量时间去研究游戏设计中一个备受争议的心理话题,即奖励安排,以及这与心理学家所谓的“过度合理化效应”有何关系。如果你从未听说过这些内容也没关系!我将在讨论它们对于游戏设计师的意义前先进行解释。

显然这些理论都适用于数字游戏和桌面角色扮演游戏,所以所有类型的游戏设计师都需要理解它们,特别是在传统桌面游戏和纸牌游戏日趋数字化的时代里。

奖励安排

在20世纪30年代,哈佛大学的一位心理学家Burrhus Frederic “B. F.” Skinner创造了一个操作性条件反射室(游戏邦注:也就是著名的“斯金纳箱”)。该理念很简单:将一只老鼠放在箱子里。让老鼠拉动箱子里的杠杆。有时候提供给老鼠一些食物让它去拉动杠杆。研究怎样的条件能让老鼠更频繁地拉动杠杆。

斯金纳箱关于奖励获取养成的实验(from gamerboom.com)

斯金纳箱关于奖励获取养成的实验(from gamerboom.com)

当然,斯金纳箱也包含冲击生物的能力,因为科学家就是这样的。

当你着眼于斯金纳箱与其它心理学家发现什么时,这一应用在游戏设计中将变得更加明确。在鸽子身上做实验的时候,研究者发现当鸽子只有一次接收奖励的机会时,它们会更频繁地推动刚刚。当它们获得奖励的机会是50%时,它们是最活跃的。这是一种间歇式奖励安排:这将给予任何特定的行动一次回报机会。研究中发现最有效的奖励安排是基于可变比例的奖励安排—-即将随机性插进等式中,如存在许多没有报酬的拉杠杆行动,但平均报酬却是固定的。

如果这一行为能够延伸到人类身上(说实话,是可以的),那么基于获得奖励的机会而不是有保证的奖励,我们便会更频繁地去执行一个活动。我们将会凭借直觉去掌握这点:这也是我们为什么会赌博。许多游戏已经使用了这些原则。举个例子来说吧,老虎机便是将“斯金纳箱子”理念带到了人类身上。Zynga因为在像《FarmVille》等社交游戏中使用可变比例的奖励安排而出名。甚至连《魔兽世界》也使用了这一理念,即让玩家不时杀掉mob而获取任务中所需要的战利品。

游戏设计众多 可变比例奖励安排的使用经常因为太过“邪恶”而遭遇批评。批评者的观点是:如果游戏设计师选择使用简单固定的奖励安排(即每个行动都伴随一个承诺奖励),玩家将只会玩一阵子。而面对可变比例奖励安排,玩家将更加活跃。因此游戏设计师是在“欺骗”玩家去玩更多他们真正想要玩的,并为此花更多钱。

在正式进入游戏中使用的可变比例奖励安排前,我想要说说在道德和奖励安排讨论中经常被忽视的另一个主要现象:过度合理化效应。

过度合理化效应

1973年,心理学家Mark Lepper和Richard Nisbett与幼儿园教师合作组织了一次有趣的实验。他们观察到孩子们会受到内在的激励去画画—-孩子们喜欢根据自己的想法去画画而不需要获得任何额外的报酬。他们将孩子们分成三个群组。他们承诺给予第一个群组的孩子缎带作为画画的奖励。也给予第二个群组的孩子缎带奖励,但却未事先说明。而第三个群组的孩子则独自在那边画画。尽管使用了缎带奖励,但所有三个群组的孩子们都交出了基本上相同数量的图画。之后他们不再提供缎带奖励。第三个群组的孩子就像他们预期的那样继续画出同样数量的图画(毕竟对他们来说什么都未发生变化)。而第一个群组的孩子在图画数量上却出现了大幅度的下降。

于是心理学家推断出,当第一个群组的孩子接收到缎带奖励时,他们的动机便从“我是因为喜欢画画而画画”(内在想法)转变成“我是因为想得到缎带而画画”。只要他们仍能收到缎带,他们就会继续画画,但一旦不再受到奖励,他们也不会再回到原先的想法了。

这是许多游戏类型经常忽视的情况。我只想分享自己亲身经历的一个例子,但如果你玩过许多电子游戏,我敢保证你将能够识别何时出现过度合理化效应。

对于我而言,在《暗黑破坏神3》中获取胜利后,我仍继续游戏,并在拍卖行中卖掉了我的稀有道具。我创建了一个出售稀有道具的商店,并在此慢慢将道具卖掉。基于这种方式我玩了好几周的游戏,但之后情况开始发生改变:暴雪发行了一个补丁,让新掉落的稀有道具变得更加强大。这让我所收集的所有道具都变得不再那么有价值,于是在阅读了这一补丁说明后我便退出了游戏。并到现在都未曾再接触游戏。这里所出现的情况是,我的动机从“我希望玩《暗黑破坏神3》”转变成“我喜欢在拍卖行中出售道具。”所有的一切在暴雪剥夺了我通过自己的努力赚钱的机会前都是很完美的。

在另外一个例子中,我玩的是《英雄联盟》,即始终致力于打开一个召唤师咒语:有名的“Flash”咒语。一旦我打开它,我便退出游戏。甚至在那之后我都未曾再玩过一次游戏。我的游戏动机从单纯地玩游戏变成了“想要打开Flash”,而一旦我做到了这点,我便发现自己不再有游戏动机了。

在这两个例子游戏,游戏都呈现给我一个目标,并逐渐破坏我玩游戏的最初想法。从设计师的角度看来这是合理的,即只要仍保留着外在动机(奖励)就足够。只要我能继续在《暗黑破坏神3》的拍卖行中出售道具,我便会继续游戏。但不幸的是,这里存在两个显著的情况将带走玩家的奖励。最简单的一个例子便是我在《英雄联盟》中的遭遇。另外一个问题就是我在《暗黑破坏神3》中经历的,即奖励逐渐过时。在这两个问题间,设计师很难在避免过度合理化效应的情况下将固定奖励安排带进游戏中。

提供奖励

在游戏中提供奖励是受欢迎的。设计师会因为各种理由给予玩家奖励,包括讲话他们的行为,提供玩家的精通感,在某一游戏过程中提升难度,支撑游戏机制和玩家能力等等。所以设计师该如何在冒着过度合理化威胁日常开支并有可能导致玩家失去对游戏兴趣的风险下提供奖励?Lepper和Nisbett在幼儿园实验中的第二组孩子便为这一问题提供了一个暗示。这一群组将在画画后获得缎带奖励,但之前却不清楚奖励的存在。在之后一旦奖励被删除,这一群组将与第一个群组基于同样的速度画画。

这能让设计师在避免将玩家动机转变成想要奖励的前提下知道该如何提供奖励。不要让玩家知道他将获得奖励—-这也被称为一种可变的奖励安排。这很直接:当玩家知道自己将获得奖励时,他便只会为了奖励而游戏。这比当奖励是不确定时转变动机更加困难。这也是为何像《魔兽争霸2》等游戏会在一些难以预测的时候给予玩家道具作为奖励的主要原因:如此玩家便可以无需依赖于奖励而好好享受游戏乐趣了。

Dota 2(from mostdangerousgamedesign)

Dota 2(from mostdangerousgamedesign)

在这里我的要点不只是澄清可变比例奖励安排不是一种内在的邪恶方法,同时还想说明它们其实是一种优秀的游戏设计实践。可变比例奖励安排并未欺骗玩家去尝试更多他们并不想玩的内容,它们是通过欺骗玩家的大脑而阻止他们从原本的游戏理由转变成外部元素。这便意味着这些奖励安排将保持玩家继续游戏,并且是因为他们发现了体验本身的乐趣,而不只是为了获取奖励,这才是真正的游戏设计!游戏设计是创造玩家能够与乐趣互动,并且无需外部理由便能够呈现出价值的系统的过程。当能够包含可变比例奖励的时候却忽略它们便等于忽略了其它已建立起来的设计理论:这只是一种卑劣的设计实践。

设计师是否能够滥用奖励安排的心理学原理?当然!大多数人的心理原理通常都会被滥用。甚至在使用心理学原理“欺骗”玩家去感受更多乐趣也算是给予玩家更多乐趣。

篇目4,Josh Bycer谈游戏设计中的内部和外部奖励设定

作者:Josh Bycer

今年,有两款截然不同的游戏发行了较大的修改补丁,它们分别是《暗黑破坏神3》和《收获日2》。它们都是基于相同的设计目的,即将人们带回游戏中去尝试全新的挑战与奖励。然而,在人们享受着《暗黑破坏神3》的乐趣时,《收获日2》却遭遇了倒彩,这也引出了游戏设计中奖励和难度设置所具有的挑战。

做出正确的修改:

在我们谈论奖励前,让我们先回顾最近的一些改变。《暗黑破坏神3》发行了补丁2.0,并为了确保战利品平衡以及为游戏准备好即将到来的扩展而基于其主机版本创造出了PC版本。这个较小的版本重新创造了战利品表去呈现循序渐进的改变。新版本重新设计了难度设置去扩展挑战而不是让游戏变得太过简单或太过复杂。

《收获日2》拥有发行商Overkill所谓的“死亡愿望”更新。首先,他们重新设计了潜行的难度级别。现在的游戏更加困难,或者在某些地图上甚至不存在任何警卫。

但最大的改变还是来自全新的难度,也就是所谓的“死亡愿望”。“死亡愿望”是《收获日2》最初的Overkill 145种难度的新版本或专家模式。在此,当你基于“死亡愿望”挑战一个游戏级别时,该级别将突出像坚不可摧的摄像机,更多障碍和更难的战斗等变化。

Payday-2(from gamasutra)

Payday-2(from gamasutra)

更难的战斗指的是将出现更多敌人,他们会更快速地移动,更快速地瞄准对象,拥有更多生命值并创造更大的伤害,并且还会出现两个新敌人。即带有沉重铠甲的精锐部队以及“skulldozer”:使用带有巨大破坏力的轻机枪的重型单位。

Overkii同样也介绍了一种新挑战:如果你能够在每个难度级别中战胜每张地图,你便能够从中获得每个独特的面具。但就像我们之前提到的,人们并不乐意看到《收获日2》的改变。

问题是双重的,一方面是因为游戏补丁添加了太多难度,另一方面则是游戏会激励或奖励接受挑战的玩家。

难度提升是一个不同的主题,我们并不打算在本文中详细说明,而奖励玩家则是我们要在此分析的内容。

归根结底就是玩家是否希望因为玩一款复杂的游戏或者更加复杂的难度而获得奖励。我知道存在一些专业玩家准备好对“玩一款复杂的游戏便能够获得奖励”做出回应,他们是对的。但其实玩一款具有挑战的电子游戏也具有其内部奖励。

战胜某种难度能够带给人们一定的兴奋感,我们可以在《忍者外传:黑之章》或《暗黑之魂》等游戏中感受到。但也存在另一种说法:创造一款复杂的游戏很简单,但创造一款具有挑战性的游戏则是另外一回事。

内部奖励:

为了让一款复杂的游戏具有内在的奖励,我们需要有效设置一些元素。首先,游戏必须让玩家觉得是公平的,而不是呈现一些不必要的难度。

像提高敌人的价值并不会改变游戏,这只意味着玩家需要花更多时间去刷任务或与敌人相抗衡。《忍者外传:黑之章》便是基于你的难度级别改变敌人而让游戏变得更加复杂的典型例子。更难对付的敌人将能更快地做出反应,拥有全新的攻击能力并且能够基于不同方式带给玩家挑战。

另外一个禁忌便是限制选择。如果你让玩家拥有各种技能,道具,但之后却说在复杂模式下他们只能使用1或2种方式战胜游戏,这便是一种矛盾。因为你将更高级别的游戏变得更加单一,并迫使玩家进入一种非黑即白的体验中。

外部奖励:

外部奖励是一个更轻松的话题。从根本上来看,任何能够提供给玩家某种奖金或奖品的内容都可以作为外部奖励的例子。所以战利品,成就,甚至是玩家角色的新图像都属于这类型奖励。外部奖励并不需要游戏做出改变,但是它们希望能够对某些内容产生影响。

比起内部奖励,外部奖励最重要的一方面便是它们需要始终都处于玩家的控制范围内。这便是玩ARPG的强制力来源:你的下一个战利品就在眼前。

在比较《镇压》和《侠盗猎车手》的收集品时,你将能看到基于正确和错误的外部奖励方式的区别。在《镇压》中,每一个敏捷的球体都能够提供给收集它们的玩家短期和长期的奖励。

而在《侠盗猎车手》系列游戏中,你在收集特殊包或在《侠盗猎车手4》中杀死鸽子时只能获得一种奖励。

也就是前者不断提供奖励,而后者只在玩家完成足够的任务时提供奖励。让我们回到《收获日2》和《暗黑破坏神3》中看看这些区别。

衡量:

《暗黑破坏神3》从最初发行到补丁2.0之间的最大改变在于奖励的派发。比起长时间未找到获得任何战利品并在之后获得非常惊人的战利品,新版本中的战利品是围绕着循序渐进的方式进行设计。所以你将能够更快地找到更棒的战利品,并且能够从最底层逐步走向更高级别。

这是创建外部奖励系统的一种正确方式,因为它将不断激励玩家向前移动。从内部看来,在《暗黑破坏神3》中体验新设计的难度关卡(游戏邦注:结合了内部和外部奖励)将让人兴奋不已。

这时候《收获日2》所面临的问题在于任何一种奖励都不能使用全新的“死亡愿望”模式。从内部来看,更高的难度在技能树以及游戏当前的装备中难以达到平衡

而从外部来看,承诺提供新的面具但却只有在经历所有强盗后才能使用。让我们列举其它可行的例子,如每次战胜一个强盗便能够打开游戏中的某些内容,如安全藏身处或专门面具,这能够激励玩家朝着更大的奖励不断前进。

哪种更好呢?

最后,我想要谈谈哪种奖励更好:内部价值还是外部价值?

这是一个有趣的问题,并且我觉得比起设计,这更多的是关于个人。就像对于我来说,比起成就我更关心挑战。

同时,我并不想玩那些只是为了难而难的内容,我想要接受那些全新且让人兴奋的挑战,并且是更简单的设置中不存在的挑战。这并不意味着我不喜欢像帽子或其它装饰物等奖励,而是我希望它们能够附加在一些有意义的行动中。

理解如何激励人们去玩你的游戏非常重要;并非所有人都是出于同样的原因去玩一款游戏。尽管同时拥有内部和外部选择很棒,但是它们也需要符合一个困难且公平的复杂系统,如此才能发挥真正的作用。

篇目5,探讨游戏奖励定义及其类型和增强方法

作者:William

在这篇文章中,我将探索奖励的基本要素。首先,我会给奖励下个定义。随后,我会阐述奖励对游戏整体意味着什么,如果游戏中的奖励不够会出现何种状况。接下来,我会列举可供游戏设计师使用的不同类型的奖励。最后,我会讨论某些让奖励发挥更大效能的方法。

奖励

奖励指那些你得到了会感觉很高兴的东西。我觉得需要对这个定义的三个层面做些许解释,即东西、得到和感到高兴。随后,还需要解释某个没有出现在定义中却需要予以重视的层面。

“东西”这个层面并不明确。无论你得到的是什么东西,只要感到高兴,就可以称为奖励。可以是有形的东西,比如一袋硬币,也可以是像在背上轻拍一下或恭维话之类无形的东西。无论游戏设计师用何种东西作为奖励,也无论你是否能够察觉到这种东西,重点在于你在得到时感到高兴即可。

“得到”这个词可能会让你觉得我的意思是奖励总是游戏给你东西的形式,但我并不是这个意思。当然,游戏中有人交给你一瓶药水确实是种得到奖励的方式。游戏中分数的提升或赠予额外的时间以及游戏开发者让你得到了有价值的经验,这些也都是你得到奖励的形式。但在某些情况下,你只是偶然遇到了奖励,这样的奖励是你自己碰上的。比如,你看到许多孩童正在玩耍,这让你的脸上浮现出了微笑。你并没有真正得到某物,游戏也没有真正给你什么,但这仍然可以视为一种奖励。所以,用“得到”这个词或许并不准确,但这确实我能想到的最接近的词。而且,在这个定义中我们也确实需要有个动词,否则定义就会显得不完整,因为奖励并不只是那些能让你感到高兴的东西。我很喜欢推拿,但除非我能得到享受推拿的机会,否则这就不能视为一种奖励。

这个定义中最重要的部分是,你因得到东西而“感到高兴”。我觉得这无需多做解释,因为我确实不知道要如何进行解释,字词便足以说明其含义。但是,我还是想要强调,在这里我们说的是种感觉。换句话说,某种东西是否可视为奖励完全是主观的想法。如果你拍了下我的头,我说道:“谢谢,这正是我所需要的”,这样你的行为对我来说就是种奖励。但是如果我对你做出同样的动作,你可能并不会和我一样将其视为奖励。重点在于,只有得到那个东西的人才能决定是否将其视为奖励。作为游戏设计师,我们可以对玩家是否将某种东西视为奖励做出合理的猜测,但我们无法下肯定的结论。我们或许会认为某个东西是种奖励,事实上玩家可能并不这样认为,反之亦然。

定义中没有提到的层面是,奖励必须赚取。如果我们要讨论电脑游戏中的奖励,我认为应该要考虑到这一点。通常玩家得到奖励的原因是做出某种行动,也就是说,玩家靠自己的行动来赚取奖励。但是,这个层面不一定存在。比如,如果某款游戏设置成规定时间过后给予玩家额外的钱币,那么玩家在游戏中就不用通过自己的行动来赚取钱币,但是如果玩家因为得到这种钱币而感到高兴,这就可以视为奖励(游戏邦注:假设所耗费的时间并非游戏中的重要因素,比如在回合制的战略游戏中)。游戏中的多数奖励必须通过赚取方能获得,但有些游戏可能出现例外情况,所有“赚取”这个词就不宜出现在定义中。但是,它对奖励的察觉确实有所影响。我将在下文具体阐述这方面的内容。

playfish-cash-game-specific-rewards(from blog.games.com)

playfish-cash-game-specific-rewards(from blog.games.com)

有价值的体验

游戏必须提供有价值的体验,否则我就不会选择玩这样的游戏。游戏必须能够提供能让我感到高兴的体验。换句话说,游戏必须带有奖励性。我们决定玩游戏的原因在于,我们希望能够因这种行为而获得奖励,感觉我们获得了有价值的体验。

奖励固然是主观的东西,但是游戏中必须要有某些能让你感到高兴的东西,否则你就不会玩这款游戏。你之所以玩《宝石迷阵》,或许是因为宝石掉落的声音能够让你感到轻松。你之所以玩《雷神之锤》,或许是因为屠杀怪物会让你感觉自己很强大。你之所以玩《文明》,或许是因为你喜欢构建帝国的感觉。你之所以玩《模拟人生》,或许是因为你喜欢游戏中只用鼠标便可以揪出坏蛋的想法。你之所以玩《网络奇兵》,或许是因为你喜欢那种极度恐慌的感觉。你之所以玩《Paradoxion》,或许是因为它让你感觉自己很睿智。无论你玩何种游戏,其原因都是你想要从中得到某些东西,某些让你感到高兴的东西(游戏邦注:即便其他人觉得这种东西很古怪)。

要让游戏提供整体性的奖励体验,游戏就必须包含某些奖励性的元素。比如,我特别讨厌别人踢我的小腿,因此你不能创造出频繁让我的小腿受到攻击的游戏,这会让我对游戏感到厌恶。游戏中必须要有让我视为奖励的东西,否则就无法给我提供有价值的体验。当然,这并不意味着要将所有的东西都设置为奖励,或者说抛弃所有让人感到厌恶的东西。毕竟,我有时也会喜欢上橄榄球或足球游戏,尽管会被人踢到小腿,我会认为这种冒犯是理所当然的游戏需求。但是,要让游戏带有奖励性,势必要在游戏中包含奖励东西。

日常琐事和挫败感

提供奖励的游戏并一定有整体的奖励性。还可能出现两种情况的偏差:游戏中有过多的讨厌之物或者游戏中奖励过少。前者会让玩家在游戏中产生挫败感,后者使玩游戏成为普通的日常琐事。

如果游戏中经常出现让你感到厌恶的东西,这样的游戏确实会令人懊恼。你的士兵经常走错路、你在游戏中碰到无法解决的谜题或者游戏总是让你失败,这些都会让人感到沮丧。砸键盘、大吼大叫或者抛掉控制器,这些起不到丝毫的作用,你在游戏中得到的奖励根本无法补偿在游戏中产生的挫败感。奇怪的是,有时我们会不顾这种挫败感,继续将游戏玩下去。或许是因为我们不甘心自己被愚蠢的电脑游戏打败!无论出于何种想法,当游戏让你产生挫败感时,你唯一要做的事情应该是:放弃这款游戏!

有时游戏不会惹恼你,但是你也没有获得奖励。这样的游戏就像是日常事务,丝毫不具趣味性。玩游戏的感觉就像你在熨衣服,这不是种惩罚,但是你也没有因为这个行为而感到高兴。通常情况下,如果游戏中的奖励出现的间隔时间太长,游戏就会变得像日常琐事一样。你花了无数分钟(游戏邦注:或者无数个小时)在森林中游走寻找魔法箱,但是你什么都没有看到,没有朋友、没有敌人更没有箱子。我会觉得这种感觉确实很无趣。或许设计师认为是奖励的东西并没有让你产生高兴的感觉。我玩《Morrowind》一段时间后产生了这种感觉。从某种程度上来说,我觉得替某些游戏内的角色完成任务并不是种冒险。我只是在遵从设计师的步伐行动。我扮演的不是个英雄,只是个跑腿的而已。对我来说,这款游戏中提供的奖励过少,所以我选择了放弃。日常琐事类游戏无疑是乏味无趣的。

奖励的类型

作为游戏设计师,我们必须关心游戏所能够提供奖励的类型。这能够帮助我们对玩家能够感到高兴的东西做出合理的猜想。游戏中存在多种类型的奖励。我知道以下所提供的奖励类型并不完整,但不完整的列表总比没有要好。以下是我所列举的奖励类型:

资源奖励。在资源有一定作用的游戏中,得到资源通常可视为一种奖励。资源可以有多种形式,包括钱币、食物、士兵、武器等。将资源奖励融入游戏中通常并不难做到,因为游戏过程需要这些资源。

技能奖励。有些游戏有明确的系统,让玩家可以提升角色的技能。比如,角色扮演游戏中提供的技能包括力量、耐力和速度。还有一种是《文明》中的科技。技能奖励让玩家产生提升的感觉。

扩展奖励。如果玩家在游戏中可能因为血量或时间的原因导致游戏结束,那么这种游戏便存在添加扩展奖励的空间。通过向玩家提供额外的生命值、生命数或时间等方式,你增加了玩家的游戏时间。玩家会将这种做法视为奖励,但是如果游戏让玩家产生上述挫败感或觉得像是日常琐事,那么扩展奖励也无法挽救这种局面。

内在奖励。如果做得好的话,图像、音乐和音效都会被玩家视为奖励。许多人喜欢看到《毁灭战士》和《Carmageddon》中的血腥画面或扑克游戏中衣着暴露的女郎。就游戏可玩性而言,内在奖励并没有为玩家提供任何东西,但是却能够使游戏体验得到升华。

成就奖励。玩家在游戏中完成某件时间,这本身就可以视为一种奖励,比如击败对手、打通关卡和配对三个粉色香蕉等。成就奖励很微妙,因为每个玩家对它们的感觉都各不相同,而且游戏初期的成就在后期或许只是常事而已。

动机奖励。尽管有时玩家在游戏中获得的东西对游戏可玩性并没有产生影响,但是这些东西能够让玩家产生动机,鼓励他们获得更多的分数。在竞赛中获胜后获得的金奖杯起到的也是这个作用。过场动画也属于这种类型,但它们所激发的不仅仅是动机。游戏内角色的鼓励性言辞或许也能够产生这种效果。

在上面列举的奖励类型中,只有资源奖励、技能奖励和扩展奖励对游戏本身能够构成影响。内在奖励、成就奖励和动机奖励都不会影响到游戏进程,但是它们能够使游戏体验更加丰富,从而对游戏产生影响。我把第一类称为游戏可玩性奖励,把第二类称为体验奖励。

reward(from pocketgod.blogspot.com)

reward(from pocketgod.blogspot.com)

奖励增强方法

对游戏设计师而言,与奖励同等重要的是,你所采用的各种用来增加奖励效果的方法。我将这些称为奖励增强方法。它们不会为游戏增添新的奖励,但它们可以让你在游戏中获得奖励后感到更加高兴。必须再次声明,以下所列举的方法并不是所有可供采取的做法。

利益增加。增强奖励的一种简单方法是增加玩家从奖励中得到的利益。在与游戏可玩性相关的奖励方面,可以提供更多的钱币、力量或时间。在体验奖励方面,可以提供更多的血腥画面或更多的分数(游戏邦注:作者认为利益增加方法无法用于成就奖励中)。利益增加的有效性有一定的局限性,超过这个临界点,玩家得到更多的利益就不会再感到更加高兴。而且,游戏可玩性奖励的利益增加有可能扰乱游戏的平衡性,所以须谨慎使用。

期盼。如果玩家在任务过程中碰到的所有游戏角色都在谈论某个漂亮的魔法石,那么玩家对这个道具的期盼值就会增加。当他最终找到时,可能会非常兴奋,告诉所有人现在他是魔法石的主人。如果没有这个期盼,玩家只会捡起魔法石然后放进背包中,完全对其置之不理。期盼也可以来源于游戏之外,比如,当所有朋友都在谈论击败最终BOSS后看到的动画时,你也会很希望自己能够看到。

成就。成就既是种奖励,也可以用来增强其他的奖励。尽管有所期盼,但是当玩家在森林中行走时发现魔法石,除了喜悦之外就没有其他特别的感觉。然而,如果他需要打败大量怪物或者通过重重障碍才能找到魔法石的所在,那么玩家找到道具时的感觉会更好。

奖品。如果你将奖励当做奖品提供给玩家,那么就预示这玩家赚取了奖励。拾取散落在关卡中的血瓶并不会让人产生获得奖品的感觉,但是通过关卡后获得额外的生命数可以产生这种感觉。奖品和成就相辅相成。玩家已经因自己的成就感觉自己获得奖励,但如果用奖品的形式提供额外的奖励,玩家肯定会感到更加高兴。

结论

奖励是某些让你感到高兴的东西。奖励是游戏的必需品,如果游戏中没有足够的奖励,会显得乏味甚至让人产生挫败感。如果你恰当地运用奖励,就可以营造出有价值的体验。你可以在游戏中使用许多种类型的奖励。而且同样重要的是,你还可以用多种方法来增强这些奖励的效果。

篇目6,从“热手”现象看游戏风险与奖励机制设计

游戏邦注:本文原作者是认知心理学博士Paul Williams,他在这篇论文中讨论了游戏设计与“热手”心理现象之间的联系,并认为深入研究“热手”现象,可为游戏的风险和奖励机制设计指明方向。

摘要:本文主要通过探讨一款游戏的风险和奖励机制设计,研究被称为“热手”的心理现象。“热手”这种表达起源于篮球运动——人们普遍认为处于热手状态的球员在一定程度上,比起他们长期的记录情况更可能再次进球,很多运动员在赛场上表现出了这种倾向。然而,大量证据认为这其实是一种站不住脚的观念。对于这种观念与有效数据存在出入的一种解释是,处于成功势头的球员因为膨胀的信心,更加乐意去冒更大的风险。我们非常有兴趣通过开发一个上下神射手的游戏来研究这种可能性。这种游戏有独特的设计要求,它包括平衡性良好的风险和奖励机制,无论玩家采取何种策略,这种机制都能为玩家提供相应的奖励。我们对这种上下神射手的迭代开发过程的描述,包括定量分析玩家如何在变化的奖励机制下冒险。我们将根据游戏设计的一般原则,进一步讨论研究所发现的意义。

关键词:风险、奖励、热手、游戏设计、认知、心理学

背景介绍

平衡风险与奖励是设计电脑游戏时的一个重要考虑因素。一个优秀的平衡风险与奖励机制可以提供很多额外游戏价值。与之类似的是赌博所带来的兴奋感。当然,当玩家如果在一个策略上打赌,他们都会持有一定的胜算和风险。打赌时,希望更大的风险能得到更多奖励的想法是很合理的。Adams不仅称“风险总是必然与奖励同在”,而且他还认为这是电脑游戏设计的基本原则。

许多游戏设计书也讨论了平衡风险与奖励在游戏中的重要性:

·“奖励与风险相当”

·创造一个复杂而进退两难的困境,让玩家自己权衡利弊,判断每一步行动可能产生的风险或者回报

·给玩家一个选择的机会,要么在奖励少的情况下安全地玩,要么在奖励多的情况下冒险,这是使游戏有趣刺激的绝妙方法。

风险与奖励在其他领域也有所体现,例如股市交易和体育。在股票市场,风险与回报总会影响投资选择。因为高风险下潜藏着高回报,所以一些投资者可能喜欢冒险投资如纳米技术这种股票。其他投资者可能更保守,选择投资浮动性更小的联邦债券,虽然得到更低的回报,但同时也承担更小的风险。在体育赛场上,因为从远距离投球能得三分,所以篮球运动员有时会采用更困难的动作来争取三分球,因此得冒更大的风险。

心理学家、认知科学家、经济学家等对这些因素非常感兴趣,总喜欢研究这些因素对人类在风险和回报结构中不同决定的影响。然而,股票市场和体育领域是喧闹的环境,这一点给玩家和研究者分离出任何事件的风险与奖励情况增加了难度。电脑游戏提供了一种卓越的平台,可以在控制良好的环境下,让人们研究风险与奖励对玩家行为的影响。我们从认知科学和游戏设计两个角度来考察风险与奖励,并相信这两个角度是互补的。心理学可以为游戏设计提供理论依据,而设计得当的游戏也可以成为心理现象研究的有利工具。

本文讨论的对象是上下神射手这种可不断更改迭代、以玩家为主心,并运用于调查“热手”心理现象的游戏。虽然本文关注的重点在于风险与奖励机制的设计过程,这种机制符合热手游戏的设计需求,我们将从这种现象的综述和目前的研究情况入手进行探讨。在随后的部分中,我们将描述游戏设计和研发的三个阶段。在最后一部分,我们会把这些发现与游戏设计的更普遍原则相互联系起来。

热手效应

“热手”的表达起源于篮球,它描述的是认为球员在进球后更有可能在下一次投篮时得分的心理现象(游戏邦注:也就是说,人们普遍认为这些球员正处于得分顺势中,投篮顺手,这种心理现象被称为“热手效应”)。在一份针对100名篮球迷的调查中,91%的人认为球员在成功投篮两次或三次后更可能再次命中,而之前如果连失几个球,以后再投篮时就不会那么顺手了。

直观的看,这些观点和预言似乎合理,开创性研究并没有发现在1980-81年的费城76人队投篮命中率,或者1980-81年和1981-82年的凯尔特队的罚球命中率中有出现热手现象。随后一系列运动研究证实了一个惊人的发现——投篮表现的冷热势可能只是一种假象。

然而,之前的投篮热手结果研究揭示了一个更加复杂的情况。之前的研究暗示,有确定困难的任务和不定困难的任务之间存在显著区别。篮球中的罚球可以作为一个确定困难的任务的例子。

在这种投篮中,距离是不变的,所以每一次投篮都有相同的难度级别。而在不确定困难的任务里,就像篮球赛中的投篮,球员可能要调整他们每一投的风险级别,所以投篮的难度会随着不同的投射距离、守势的压力和整个比赛的情况而改变。

有证据表明,玩家可能在确定难度的任务,例如掷马蹄铁、台球和十瓶式保龄球中获得顺势。然而,在非固定难度的任务里,例如棒球、篮球和高尔夫球,这种冷热势并不明显——其实际情况与普遍观念相反。

对于流行观念和真实数据之间不一致的最普遍解释是,人类往往误读了数字中的小趋向模式。也就是说,我们倾向于形成基于几个事件组的模式,例如球员三连投,然后用这种模式来预测随后的情况。关于投篮,经过三次成功的投球后,人们会错误地认为下一个投射比起长期水准更可能成功。这就是顺势的谬误。

关于这种不一致的另一种解释表明,为了不产生失误,投球者在一连串的成功中往往要冒更大的风险。在这种情形下,一个球员在热手情况下确实表现更好—–因为他们在相同准确度的条件下承担了更困难的任务。这种能力的增强恰好印证了热手预言,然而传统的投篮表现纪录却没有发现这一点。尽管我们通过界定固定难度和非固定难度之间的区别(因为热手情况多发生于固定难度的任务中,运动员所面临的是难度固定的挑战),可以让这种假设暂时成立,但只有进一步的研究才能证实这种假设究竟是否站得住脚。

不幸的是,如果设法收集更多运动比赛中的数据来研究热手现象,则不免带有主观性因素。我们如何评估一个确定投射的难度超过另一个投射呢?如何辨别球员是否采取了更有风险的策略?

解决这个问题的一个好办法就是,设计出可以准确记录玩家策略变化、难度不定的电脑游戏。这种游戏或许可以回答与心理学和游戏设计相关的重要问题—-玩家如何对游戏中一连串的成功或失败做出反应?

这款“热手游戏”的开发过程正是本文讨论的重点。这种游戏需要一个非常协调的风险和奖励机制,并通过玩家所采取的冒险行为,不断调整游戏结构。在各个开发阶段,我们测试了玩家对风险和奖励机制作出的反应,然后按照玩家的策略和表现,分析这些结果,以便将其运用于下一阶段的游戏设计。

这种设计的特征是反复性、以玩家为主心。虽然本文所示的游戏设计比较简单,但考虑到心理学调查地准确性的要求,我们执行的是比一般游戏开发更为规范的玩家测试。结果发现,我们可以准确评估玩家策略的改变,发现即使是风险与奖励机制中的微小变化,也会对玩家的风险策略产生影响。

游戏要求和基本设计

这种热手游戏首先需要一个相当协调的风险和奖励机制,它必须具备几个(5-7)高度协调的风险级别,使得玩家乐于调整他们的冒险级别来应对成功和失败。比如,一个风险级别得到的奖励实际上多过其他的风险级别,玩家久而久之会学到这点,然后就不太可能在这个级别中改变策略了。所以我们希望每个风险级别都能让普遍玩家都得到相应奖励。换句话说,不论采用什么风险级别,玩家得到最佳奖励的机会应该是相等的。

第二个要求是,支持我们在玩家成功和失败后对其策略进行考察。如果玩家经常失败,我们就无法记录足够的成功次数。如果玩家大多时候成功了,我们就考察不了失败情况。所以这个游戏的核心要素和关键难度在于,提供平均的成功概率,其范围介于40-60%。

满足这些要求的是使用Actionscript在Flash环境中开发的上下神射手游戏。任何基于物理挑战,带有得失分的简单动作类游戏都适用于我们的研究,上下神射手则恰好具有这几个优势。首先,人们这种风格的游戏极为熟悉,这意味着玩家容易上手,有助于我们用这个游戏来收集实验数据。第二,简单的重点难度参数编码(即目标速度和加速度),可以使我们轻松而准确地操作奖励机制。最后,上下神射手游戏中的“一击”与篮球中的“一投”相类似,有相似的“命中”和“错失”结果。这就是当前实验与热手起源之间的联系所在。

在上下神射手游戏中,玩家的目标是在规定的时间内尽可能多地射击外星飞船。也就是说总射击量和命中数量取决于玩家的表现和策略。游戏的屏幕会显示两架飞船,代表外星人的飞船和玩家的射击机(图1)。简单的界面显示了当前命中数和所剩时间。在游戏过程中,玩家的飞船会在屏幕底部中间保持静止。任何时候屏幕都会只出现一架外星飞船,它会在屏幕上部水平地前后运动,并且每次返回都碰一下右边沿或左边沿。玩家按下空格键即向向外星飞船射击。玩家只有一次机会来摧毁每一架新出现的外星飞船。每击落一架外星飞船,玩家就得到一个命中数的奖励。

每一架外星飞船都是从屏幕上方进入游戏界面,随机向左边沿或右边沿移动。飞船飞离屏幕两边,水平移动,如此经过八次后才会离开屏幕。最初,外星飞船移动飞快,但它以相同的速率减速,每一次经过都更加缓慢。因此这个游戏能够展示一种不同难度的任务;玩家可以选择适合的风险级别,这样每次外星飞船经过时射击就更简单些。

对于玩家来说,这种风险和奖励的等式相当简单。无论玩家何时开火,每一次命中的得分都是一样的。因为目标是在一个游戏周期里摧毁尽可能多的外星飞船,所以玩家可以尽快从射击中获利;越早射中目标,玩家不仅得到命中数,同时获得更多的时间来击落随后的外星飞船。然而,因为外星飞船在八次经过的每一次经过里都减速,玩家越早开火就越难命中。如果射空了,玩家就减少1.5秒作为惩罚。也就是,下一架飞船的出现只有1.5秒的延迟,这就增加了准确射击的间隔时间。

第一阶段:玩家锁定目标

经过自测游戏,我们将游戏拓展到在线版。通过向学生、家庭和朋友发电子邮件,我们找到了五名实验玩家。我们要求玩家在给定时间内击落尽可能多的外星飞船。玩家先在练习级别上试玩6分钟,然后在竞技级别上玩12分钟。因为玩家的策略和命中率存在差别,所以他们遇到的外星飞船数量也各不相同。一个玩家有可能在60秒内遇到大约10架外星飞船。游戏结束后,玩家对每架外星飞船的反应时间和命中率都被记录在案。

游戏的要求之一是,玩家在一系列难度级别中射击经过的飞船(越后面的飞船经过意味着更低的射击难度——这种简单的测试证明了在整个游戏中,玩家乐意探索空间,并且改变他们的冒险行为。图2是代表玩家1和玩家2的结果。通常玩家在游戏的练习级别时往往很有探索精神,这显示在第一次经过和第八次经过之间的射击数分布。然而在竞技级别,玩家往往采用单一策略,从图2的大尖峰可以看出来。它暗示了玩家在经过探索期后,试图通过射击三个固定的飞船经过以获得更多得分。

图2:玩家首次测试结果(from gamerboom.com)

图2:玩家首次测试结果(from gamerboom.com)

上图是两名玩家在游戏第一阶段的测试结果。玩家1数据显示在上部,玩家2的数据显示在下部。左边的柱形代表在练习阶段的射击频率;右边则代表在竞技阶级中各个经过的射击频率。受测玩家在练习模块,射击频率均匀地分布在各个飞船经过,如左边图所示。但之后在竞技模块中,玩家采取固定策略,右半边的图中的尖峰正体现了这种情况。在以上各图中,n代表玩家的尝试射击总数;m代表命中数,sd代表尝试射击数的标准差。

在实验术语里,守定一个策略的行为被称为“投资”。在游戏结束时玩家反映,因为飞船的匀速减速,那么如果他们锁定同一次飞船经过,且与边界达到特定距离,就总能射中目标。针地特定经过的外星飞船,玩家采用特定的限时策略(即一个特定的难度级别)。在同一次飞船经过的射击中,玩家在每个时间单元里的命中数总是最高的。在案例表格(图2)里,一个玩家“投资”于第四次经过,另一个则是第五次经过。这种类型的投资行为与热手游戏的一个要求相反,也暴露了游戏的一个主要设计缺陷,这需要在下一个迭代调整中进行修正。

第二阶段:鼓励玩家探索

游戏设计第二个阶段的目标是解决玩家在单一策略上的投资问题。我们提议的解决办法是改变玩家飞船的位置,这样它就不再出现在屏幕中间那个相同位置了,而是在每架外星飞船出现时随机转移到中间的左边或右边(图3)。这样,在每一次测试,玩家飞船的位置都从平均分布的100像素中心的左边或右边中随机移动。这个操作旨在防止玩家习惯单一策略,总是等待凑效的时间序列采取行动(例如总是在飞船第四次经过,与屏幕边沿有固定距离时射击)。

上图是游戏第二阶段的屏幕。蓝色矩形出现在这里是为了指明玩家飞船可以随机定位的范围,但在真正的游戏过程中不会出现这个蓝色矩形。

这一次我们推出了这个游戏的在线版本,并记录了6个玩家的测试数据。再次让他们先在练习级别上试玩6分钟,之后在竞技级别上玩12分钟。

各个玩家在竞技级别的结果显示在图4上。在玩家射击位置里引入随机变化,显著减少了玩家投资于同一次飞船经过的倾向。与图2相比,图4变化的增加突显了投资的减少。因此,游戏中的微小调整对玩家的行为产生了重要影响,它鼓励玩家在游戏中改变冒险策略。另外,这种调整满足了热手研究的必备要求。

图4:玩家改进策略(from gamerboom.com)

图4:玩家改进策略(from gamerboom.com)

上图是玩家在测试第二阶段中竞技级别的个人结果。减少的峰值和变化的增加表明,与第一阶段相比,玩家在竞技级别的单次飞船经过中射击的倾向大大减少。以上各图,n代表玩家的尝试射击总数;m代表命中数,sd代表尝试射击数的标准差。

图5代表所有的玩家在练习级别和竞技级别的平均测试数据。所有玩家在练习和竞技级别中的平均数据,均突出了游戏奖励机制对玩家游戏策略的影响。左边的柱形代表练习级别(没有在图4中显示)的数据,右边则代表竞技级别的数据。

图5:玩家推迟射击

图5:玩家推迟射击

上图是第二阶段中玩家的平均数据结果。左边的柱形图代表在练习级别每一次飞船经过的射击频率(%),右边则显示了在竞技级别每一次飞船经过的射击频率(%)。在以上各图中,n是所有玩家在该模块中尝试射击的总数;m是平均命中数。练习级别和竞技级别的射击对比,突出了玩家在游戏进程中推迟射击的趋势。

图5显示随着游戏的推进,玩家的射击策略有预见性地发生改变。例如,在练习级别的平均命中数(m=5.8)比竞技级别的(m=6.21)更少。这样在竞技级别,玩家往往更迟发动射击。这表明游戏奖励总集中于后面几次飞船经过,而玩家越来越熟悉这种奖励机制时,就会相应地调整游戏玩法。

为了在热手研究中最小化这种偏差,我们在平均玩家表现的基础上检测了风险与回报机制。我们特别感兴趣的是,第一次成功射击的可能性以及这种可能性如何转换为奖励系统。在后面的飞船经过中射击要花更多时间,但与之相伴的是更高的命中率。因为热手游戏的目标是在12分钟内击中尽可能多的外星飞船,所以命中率与所花时间对奖励机制来说具有同等重要性。

之后我们分析了一种情况,假如玩家坚持在特定的飞船经过里射击各个出现的飞船,那么12分钟内,平均命中数是多少。例如,在发现第一飞船经过的命中率后,玩家在第一次经过中会采取几次射击行动?第二次飞船经过时呢?以此类推,其后几次飞船经过的情况又将如何?图6显示了这个检测的结果。图6A显示了玩家在几次飞船经过时射击的平均数(柱形的总高度),以及每一次飞船经过的命中数(柱形黄色部分的高度)。图6B用这份数据表现成功的可能性,并且表明在后面几次的飞船经过中,玩家成功的概率更高。这从实验上证实,玩家在心理上感觉,后面几次飞船经过更容易让他们射中目标。

图6:预测玩家命中率(from gamerboom.com)

图6:预测玩家命中率(from gamerboom.com)

上图是游戏进程的第二阶段中的平均数据和模型预测。在图A,每个矩形的总高度表示尝试射击频率。黄色和蓝色矩形的高度表示命中和错失比例。图B表现的是给定尝试射击总数,每一次飞船经过命中的平均概率。图C和图D在实验结果的基础上,预测了假如玩家自始至终只在一次飞船经过时射击的命中数量。

这些可能性评估了在全程12分钟的模块里,只在一次从飞船经过中射击的情况下,一般玩家可能取得的总命中数。通过演示每次经过的期望命中数,我们为当前的游戏画出了一个最佳的策略曲线,如图6C所示。这个曲线是单调递增的,表明随着经过次数的增加,平均玩家的总命中数也随之增加。换句话说,玩家在低难度射击中更可能命中。游戏奖励明显集中于后面的飞船经过次数,这证实了玩家在游戏过程中改变了策略(即推后射击)。随着对奖励机制的熟悉,玩家的策略也相应地转向更迟,更容易的射击机会。

对游戏而言,在第8次飞船经过时射击可以认为是一种探索策略。图6C表明不断地在第8次飞船经过时进行射击产生了最大命中数,这也因此成了玩家的普遍策略。因为形成了这种策略,玩家为了获得一连串命中,就会减少早点射击的次数。可见这种设计仍然不能满足热手游戏的要求。

但只要一个简单的调整就能解决这个问题,那就是减少失败射击后的惩罚等待时间。目前惩罚时间是1.5秒,所以应该允许奖励机制中的惩罚时间发生一定的弹性变化。考虑到如果玩家选择在早一点的飞船经过时射击,击射次数越多,失误也就越多——减少每一次失误的惩罚时间,实际上等于是增加了在早期飞船经过时进行射击的奖励。

图6D表现的是在惩罚时间从1.5秒减少到0.25秒的情况下,一般玩家在12分钟里的预测命中数。这看似很小的调整平衡了奖励机制,这样玩家就得到更平衡的奖励(游戏邦注:至少从第3次飞船经过到第8次飞船经过是这样的)。对第一次飞船经过和第二次飞船经过准确率的评估是以小次数测试为基础的,这使它们难以成为测试模型;玩家避免采取更早的射击行动,有可能是因为外星飞船移动得太快。但允许玩家在第3次到第8次飞船经过中射击,仍然可为我们的热手研究提供了足够的参考数据。

第三阶段:平衡风险与奖励机制

在游戏设计的第二阶段,我们展示了玩家在飞船第8次经过时取得最佳表现的风险与奖励探索策略。我们认为这有可能就是促使玩家在飞船后面经过时射击的原因。可以用实验数据来模拟玩家表现,表明将惩罚时间降至0.25秒就能解决这个问题。

在改良版的在线游戏中,惩罚时间是0.25秒,五位玩家的测试数据均已一一记录。平均结果显示,在练习和竞技级别,玩家的射击大致发生在相同的飞船经过次数里(图7)。这个特征与图4相反,后者突显玩家在12分钟的竞技级别中,呈现了在飞船后面经过时才射击的倾向。这组数据证实了选择0.25秒惩罚时间的正确性,同时也证实了奖励机制的改变,可能影响玩家行为的说法。

图7:改变奖励机制的影响(from gamerboom.com)

图7:改变奖励机制的影响(from gamerboom.com)

图7:游戏第三阶段玩家的平均数据结果。左图代表玩家在练习级别的各次飞船经过的射击频率;右图代表玩家在竞技级别的各次飞船经过的射击频率。在以上各图中,m是平均命中率,n是玩家在该模块的总射击数。平均命中率显示了在均衡的奖励机制下,玩家不再尝试推迟射击。

我们开发热手游戏的前提条件就是,游戏在每一个假定风险级别中,都应该为一般玩家提供相应的奖励(总命中数)。第三阶段起的设计通过平衡奖励制度,开始与研究热手现象的要求保持一致。

最后,我们要求这个游戏有一个总体上的难度级别,使玩家的尝试射击有40-60%的成功率。这个范围内的表现,有助于我们综合比较玩家对应一连串成功和失败的策略。也就是,对热势和冷势的测试。图8突出总体成功概率确实满足这个标准,总体成功概率(命中率)是43%。因此,这个游戏现在满足了研究热手现象的必要条件。

图8:第三阶段平均结果(from gamerboom.com)

图8:第三阶段平均结果(from gamerboom.com)

图8:游戏开发第三阶段的竞技级别的平均结果。在图A,每一块矩形的总高度代表玩家在每一次飞船经过时尝试射击的频率。命中和错失比例分别用黄色和蓝色表示。图B是根据总体射击次数的情况,显示每一次飞船经过时的平均射击成功概率。在图B里,ps是总体成功概率(命中率)。

总结

为了研究热手心理现象,我们才开发这个电脑游戏作为研究工具,需要以此观察玩家对一连串成功和失败挑战的冒险反应。

我们设计了一款简单的上下神射手游戏,在该游戏中,外星飞船在屏幕上来回经过8次,玩家只有1次射击机会。玩家在游戏中面对几次相同的挑战。该游戏的目标是在一系列时间段内击落尽可能多的外星飞船。随着飞船减速,游戏设置里的风险就相应减小。玩家在靠前的飞船经过时成功击落目标就可获得1个命中的奖励,并且立即出现新的外星飞船。错失一次射击,就以一段额外的等待时间作为对玩家的惩罚。

作为一款热手游戏,它需要达到特殊的冒险和奖励标准。玩家需要在游戏中探索一系列冒险策略,并且均衡地获得与风险级别相当的奖励。我们还希望这个游戏挑战有一个与失败率大致相当的平均成功率,即介于40-60%,这样我们就可以用这个游戏来收集玩家应对成功和失败的行为数据。

为了达到目的,我们开发了超过三个阶段的迭代游戏版本。在每一个阶段,我们都通过在线版游戏的测试收集实验数据,并分析玩家的策略和表现。在各个后续设计阶段,我们都调整了游戏机制,使其在一定程度上达到平衡,以满足热手游戏的特殊要求。这个游戏设计的调整及其影响总结如表1所示。

表1:实验总结(from gamerboom.com)

表1:实验总结(from gamerboom.com)

表1总结:各阶段的设计调整及其对热手实验要求的影响。

游戏设计书往往会描述出游戏迭代的设计过程。这种迭代过程支持设计者在后继开发阶段解决原先没有预料到的问题。由于游戏机制在开发之初并不明朗,只有在游戏创建和操作阶段才突显

出来,因此迭代过程对游戏的完善来说尤其重要。Salen和Zimmerman将这种迭代过程描述为“以试玩为基础“的设计,同时强调了”游戏测试和创建原型“的重要性。为了实现目标,开发者往往需要连续创建游戏原型。我们确实是以高要求开始用相同的迭代完善、创建原型方法来改进我们的游戏设置。

我们这个方法的主要不同点在于,我们在各个设计阶段都会更规范地测验玩家的策略和探索行为。考虑到我们的游戏要求相当独特,单纯的客观反馈无法支持我们对游戏机制的需求进行微小调整。比如,在最初的测试里,我们发现玩家倾向于单一的游戏策略。进一步的分析也表明玩家通过射击最后一次经过的飞船,可以容易地增加他们的总体命中数,这是玩家对游戏策略的潜在开发。

游戏策略的探索问题在游戏界常引起争议,并屡屡被作为心理学界研究对象。开发和探索之间的权衡现象在许多领域也存在,外部和内部条件决定了玩家为扩大最大利益,或者最小化损失所采取的策略。例如,在寻找食物过程中,玩家就会关注资源分布情况。集中的资源,会让玩家集中对资源丰富的就近地区进行开发,而分散的资源则会将玩家引向对空间的探索过程。

Hills等人表明,探索和开发策略在精神领域也存在竞争,这取决于对需求信息的奖励,以及为研究探索所付出的代价。在我们的游戏环境里,玩家始终在最容易的情况下(即飞船第8次经过时)射击的这种策略总会产生最高的奖励。这就鼓励了玩家在游戏中采取推迟射击的策略,反过来也抑制了玩家探索其他策略(更早的射击)的尝试。如果没有收集玩家的实验数据,我们不可能预测到这个结果。

收集实验数据的另一大优点在于,它支持我们在衡量玩家表现的基础上,改变我们的奖励制度。在第一和第二阶段,每次损失1.5秒,玩家就会错失一个外星飞船。在第三阶段,我们在分析

玩家表现的基础上,将惩罚时间降至0.25秒。这个微小的调整却足以改变玩家的行为,并鼓励他们更早地冒险射击外星飞船。我们的游戏从本质上来看是相当简单的,但它却足以证实设计一个平衡性良好的冒险与奖励机制的困难性和重要性。

其他游戏文献里谈到的另一个共同的设计原则是以玩家为中心,这被Adams定义为“一种由设计者想象自己所希望遇到的玩家类型的设计哲学。”尽管如此,还是有一些观点认为游戏设计通常是以设计者的经验为基础。将玩家纳入设计过程往往也涉及更多客观反馈,例如将中心群体和采访广泛运用于可用性设计。我们在研究中发现,即使是很简单的游戏挑战,使用实验数据来测验玩家如何应对游戏以及他们如何表现,这也会成为平衡游戏设置的一个重要元素。

我们也认识到这种方法有一些缺点,即平均考察每位玩家的表现,有可能忽略玩家之间的重要差异。如果有一个理想的玩家模型就太好了,但这种玩家是不可能存在的,事实上,关于谁是“玩家”这个问题本身就存在许多富有争议的不同观点,因此我们才需要收集不同玩家群体的实验数据。如果玩家之间的差异很大,设计者有可能得针对不同群体进行抽样调查,例如将其分为休闲玩家、硬核玩家等不同群体。

现在我们所完成的游戏设计已满足研究热手现象的要求。这个游戏也许可以回答以下几个问题:

1.在游戏挑战中,玩家如何对一连串的成功或失败作出反应?

2.如果玩家处于热势,他们会接受更困难的挑战吗?

3.如果玩家处于冷势,他们是否会降低风险?

4.这种多变的风险级别如何影响玩家表现的总体测验?

5.热手原则如何运用到游戏机制设计中?

相信关于这些问题的答案不仅会激发心理学家的研究兴趣,而且也能进一步促进游戏设计。例如,设计者可以激起玩家的热势,使其更倾向冒险或探索他们的策略。当然也有可能运用冷势来抑制玩家当前策略,这种游戏机制可以在不打断玩家注意力的情况下,不知不觉地控制玩家的冷热势。进一步探索热手现象,将对心理学研究和游戏设计产生重大意义。

篇目1篇目2篇目3篇目4篇目5篇目6(本文由游戏邦编译,转载请注明来源,或咨询微信zhengjintiao)

篇目2,The Hierarchy of Needs for Rewards in Games

[Chelsey Webster explains how a skillfully implemented reward structure can enhance a player's experience and make a game more enjoyable throughout.]

Introduction

Rewards are an important feature of any game, and as such, can be found everywhere across all genres. Rewards can come in any shape or size, and when given to the player appropriately can greatly increase their enjoyment of a game, motivating them to continue to play.

Rewards can even have a player do something that they don’t want to do, or don’t enjoy doing (which is quite opposite of the purpose of playing a game). Many players will do annoying, tedious or boring things for rewards. The ability to have a player do what they dislike of their own volition attests to their power. They are an essential tool to a designer.

Designing Reward Structures

Rewards shouldn’t be included on a whim; they must be scheduled and structured. The following diagram is a hierarchy of needs, adapted for reward structures.

Fig 1: Hierarchy of Rewards in Games

Based on Maslow’s Hierarchy of Needs, each section is a prerequisite to the one above, and can greatly enhance the one below. If a section is missing, however, those above it become ineffective.

When designing a reward structure, it is important to work from the bottom of the hierarchy upwards to achieve a solid foundation. It is therefore important that each section is linked to the next.

The higher up in the hierarchy, the more frequently the reward should be distributed; a fractal-like pattern should emerge (i.e. 10 minor rewards = 1 major reward, 10 major rewards = 1 core reward). It doesn’t have to be strictly fractal of course, but minor rewards should considerably outnumber major rewards, and so on.

As we move upwards through the hierarchy, rewards become less intrinsic/more tangible. The bottom of the hierarchy is the most fundamental and intrinsic of rewards to the player – the player experience. At the other end of the scale, the top is purely cosmetic and cannot exist without the rewards listed below – however it works to enhance those below. Think of a scope for a rifle. The scope is great, and makes the gun much better; but it is completely worthless without the gun.

The following gives an overview of each section of the hierarchy and what kind of rewards may be found therein. Examples here will often be of the kind found in adventure or RPG games, but the principles can be applied to any genre. The rewards structure should always be designed in order of importance – from bottom to top.

Rewarding Player Experience:

Before considering anything else in detail, the player experience must be perfected. Good gameplay and immersion must first be obtained through the mechanics, aesthetics and UI (including essential player feedback). It is difficult to define whether this section is fulfilled, as fun is something that can only be experienced. The player must enjoy simply playing around with the game. The Grand Theft Auto franchise achieves this very well – who hasn’t switched it on, then ignored the missions and started wreaking havoc until they’re killed? There is no set goal to this, no rewards given (in fact the player is punished by losing ammo and paying hospital bills), but people do it because the gameplay/mechanics themselves are so much fun and intrinsically rewarding. Few games are fun to the extent that a person will play them with no prospect of rewards at all. Perhaps this is why GTA is so successful.

Core and Long Term Rewards:

Once the player experience is perfected, consider the core/long term rewards. These are very big rewards that the player will have forever. Examples include major plot developments, major milestones in opening new content (reaching a new island in Grand Theft Auto for example), or receiving a new game mechanic, such as those given after every boss fight in Crash Bandicoot 3. As these are the biggest tangible rewards that the player will receive and can affect the intrinsic experience, they should be given only occasionally. This retains their value and prevents annoying the player. People would become frustrated if they earned a new ability every 10 minutes; they’d never learn how to play.

Major and Mid Term Rewards:

These may be levelling up, completing quests, gaining large quantities of XP or money, etc. These rewards are significant to the player at the time but are not end rewards that are kept forever.

They are very rewarding in themselves, but are also means to and end and will eventually be overwritten, replaced or become redundant.

Short Term and Minor Rewards:

These are small, frequent rewards which on their own do not benefit the player, but accumulate towards a bigger reward. Examples include collecting an item, small amounts of money/XP for defeating an enemy, or completing a stage in a mission. Just as Major rewards are means to a bigger end, Minor rewards are also means to an end on a smaller scale (the end being major/mid term rewards).

Cosmetic Rewards:

This is the final section to be considered. At the top of the hierarchy, they are purely cosmetic, serving only as a visual measure of the player’s progress. In some cases they are simply informative, such as numbers appearing on screen when you add to your score, or the squad selection screen in Mass Effect – the player can guess that they’re about halfway through when they’ve filled half of their squad slots.

On the other hand, visual progress elements such as unveiling a map or filling a bar can actively encourage players to do things that they would not do otherwise, as can achievements depending on design. A player might play for 10 minutes longer where they would have otherwise stopped because their XP bar shows them how close they are to levelling up. They may not attempt to round up and defeat 10 enemies with 1 grenade if there was not an achievement challenging them to do so, and may not just run around the entire area if they weren’t revealing their map.

While a game can still be enjoyable if the cosmetic rewards are removed, they will enhance the player experience as players like to see how they’re doing. Visual rewards are vital in helping the player to gauge and anticipate rewards which is an encouraging motivator. Visual rewards never actually affect progress or any other aspect of the game at all.

There is a blurred line between the player feedback (mentioned at the bottom of the hierarchy), and cosmetic rewards (at the top). Player feedback is essential communication to the player, but cosmetic rewards can exist on their own (as with achievements, etc), or tie into player feedback for visual enrichment. One big difference between the two is that omitting essential player feedback can be game breaking, or at least break immersion. An example of essential feedback is seeing your avatar animate as you move around in the world. if it simply floated across the landscape this would completely break immersion and make it unplayable to many players. A problem like this is found to an extent in Oblivion and Fallout 3 (3rd person). The avatar animates but not it doesn’t match its direction if running diagonally, so the character appears to float around. When playing in 3rd person this can completely break immersion. You can see an example of this here.

While it should be designed bottom up, the player will often experience much of this hierarchy from a top down perspective. They will experience cosmetic elements and minor rewards to begin, such as obtaining a task (this is where they are initially given the prospect of rewards), then minor rewards such as collecting items and XP, which lead to major rewards earned by completing the quest or levelling up, and eventually core rewards such as a new mechanic or unlocking a new world.

Application to a successful game:

This hierarchy includes rewards featured in World of Warcraft, a very popular (and notoriously addictive) game.

Fig 2: A Basic reward structure of World of Warcraft

(does not include all rewards)

These are just a selection of the rewards offered, but it is clear that the game is abundant in rewards on every level. The world and the gameplay are immersive and such high customisation of the player experience (classes, specialisations, PVP/PvE, RP, and so on) means there are hundreds of player experience combinations in one game.

Add to this the limitless supply of rewards of all kinds which all tie in to one another and accumulate towards something. Then, to top it off it is peppered with random chance rewards. Even the most mundane creature can drop disproportionately powerful rewards on very rare occasions. There is always a reason to keep playing; this is clearly a very strong reward structure in every aspect.

Application to an unsuccessful game:

As part of an experiment for my dissertation I created a very simple 2D space shooter game. Though it was fit for the purpose of an experiment on rewards and yielded conclusive results, the game would not be popular or successful in the real world. After developing this hierarchy I decided to apply it to my game:

Fig 3: Reward structure of a basic 2D space shooter

The game is strong at the top and gets weaker as we get to the fundamentals of the hierarchy. There is no hope for this game on the market today no matter how good the upper sections are, because the lower sections are not fulfilled. As well as gameplay being lacklustre, an entire section is missing. Tight time and resource limitations meant that the game focused on tangible rewards which could be created quickly and easily. There was no time to invest in excellent gameplay; it just had to work.

It is easy to draw a comparison between this game and popular arcade games from the 70′s. These were successful in their day, though they did include the long term reward of top slot on the leaderboards – but today their main appeal is arguably nostalgia. Todays games have far more sophisticated gameplay and reward structures, so a game like this cannot compete.

Consider the World of Warcraft hierarchy if a section is missing:

Fig 4: World of Warcraft’s reward structure with a section removed.

With this section missing, the hierarchy doesn’t make much sense. Level increments are gone, for example, so now the player must go from level 1 to level 90 (or whatever its new name would be) in one grind. The player would be consistently weak and the suddenly immensely powerful, but only after an inordinate amount of time. Needing 999,000,000,000 XP to reach the next/last level is far too discouraging when the player is getting 20XP per enemy, even more so when their XP bar never seems to budge. Bitesized chunks are essential.

The removal of this section has completely devalued those above. The minor and visual rewards contribute so little to the next goal that they don’t feel very rewarding at all. Players are much happier and more likely to play if they feel that their goal is realistically obtainable.

Summary

Quality does not equal quantity, but it is important to have at the very least one reward in each section. Aim to fulfil each section of this hierarchy to a high standard and ensure that they accumulate towards one another. Though it has not been around long enough to be tried and tested on a large scale, following this structure should achieve a strong, structured, rewarding player experience.

While many of the examples throughout this article are based on action adventure/RPG type games, they can be applied across any genre, from puzzle games to sports and racing. By applying this model when designing a reward structure, the designer can ensure that the game has solid foundations and is rewarding enough to make the player feel good. This can ultimately keep them playing the game.

篇目3,The Psychology of Rewards in Games

by Max Seidman

Over the past 2 years I’ve had the privilege of working with at Tiltfactor alongside Dr. Geoff Kaufman, who has a PhD in social psychology and is our head of research at the lab. In addition to the fantastic insights he has made running formal studies on the games we’ve been developing (publication pending on those), I’ve learned amazing things about psychology, formed many theories about how it influences game playing, and developed a list of things game designers need to keep in mind. I’ve devoted a lot of thought recently to one of game design’s most hotly debated psychological topics, reward schedules, and how they relate to what psychologists call the “overjustification effect.” But don’t worry if you’ve never heard of either of these things! I’ll explain them both before discussing what they mean for game designers.

These theories, while most obviously applicable to digital games and tabletop roleplaying games, are important for all types of game designers to understand, especially in an era where even traditional board and card games are becoming more digital.

Reward Schedules

In the 1930s, Burrhus Frederic “B. F.” Skinner, a psychologist at Harvard, invented an Operant Conditioning Chamber (better known as a Skinner Box). The concept was simple: put a rat in the box. Let the rat pull the lever in the box. Sometimes give the rat a food pellet for pulling the lever. Study what conditions cause the rat to pull the lever more or less often.

Of course Skinner Boxes also include the capacity to shock the creature because scientists are freaky like that.

The applications in game design become clear when you look at what Skinner and other psychologists found. While experimenting with pigeons, researchers found that the pigeons were more likely to push the lever more often when there was a only a chance that they would receive a reward, even more often than when they always received one. Specifically, they were most active when the chance of receiving a reward was 50%. This is an intermittent reward schedule: it gives a chance at payoff for any given action. Specifically, they found that the most effective reward schedule was a variable ratio reward schedule – inserting randomness into the equation such that there could be many pulls of the lever with no payoff, but the average payoff is set.

If this behavior can be extended to humans (and let’s be honest, it can), we can be controlled to perform an activity more often simply by giving us a chance at a reward instead of promising us a guaranteed reward. We tend to know this intuitively: it’s why we gamble. And tons of games already use these principles. For example, slot machines are basically Skinner Boxes for humans. Zynga is notorious for using variable ratio reward schedules in their social games like Farmville. Even World of Warcraft uses them by having killed mobs only drop the loot you need for quests some of the time and not all of the time.

Skinner Box for people

The use of variable ratio reward schedules in game design is often panned, however, for being “nefarious.” Detractors’ reasoning goes: if the game designers had chosen to use simple fixed reward schedules (where for each action there is a promised reward), the players would play a certain amount. With variable ratio reward schedules, the players are more active. Thus, the game designers are “tricking” the players into playing more than they really want to, and usually also spending money.

Before I go into the ethics of using variable ratio reward schedules in games, I want to talk about another crucial phenomenon that is often overlooked in discussions of morality and reward schedules: the overjustification effect.

Overjustification

In 1973 psychologists Mark Lepper and Richard Nisbett conducted a fascinating experiment with kindergarteners. They observed that the children were intrinsically motivated to draw —that the kids enjoyed the activity of drawing pictures for its own sake without any need for external payoff. They split the children into three groups. The students in the first group were promised ribbons as a reward for drawing. The students in the second group were given ribbons, but were not promised them beforehand. The third group was left alone to draw in peace. While the experimenters handed out ribbons, all three groups drew comparable amounts of drawings. Then they stopped giving out ribbons. The third group, as would be expected, continued to draw the same amount (after all, nothing had changed.) The first group, however, had a significant drop off in the amount of drawing they did.

Psychologists theorize (and they’re pretty certain at this point) that what happened is as the first group received ribbons, they shifted their motivations from “I’m drawing because I like drawing” (intrinsic) to “I’m drawing because I want a ribbon.” They were still motivated to draw so long as they were receiving their rewards, but once the rewards were removed the motivation did not snap back to being intrinsic.

This is an often overlooked phenomenon that occurs in many sorts of games. I only have personal anecdotes to share, but if you play many video games I’m sure you’ll be able to identify times when the overjustification effect happened to you.

For myself, after beating Diablo 3 I continued to play and sell my rare items for money on their real money auction house. I built up quite a store of rare items that I was slowly selling off. I played this way for several weeks, but then something changed: Blizzard released a patch making newly dropped rare items much more powerful. This made all of my collection worthless, and I quit after reading about the patch. I haven’t played since. What happened here was I shifted my motivation from “I like playing Diablo 3” to “I like selling items on the auction house.” This was all well and good until Blizzard took away my chance to cash in on my efforts, and then I simply quit.

In another personal example, I played League of Legends, all the while working towards unlocking a single summoner spell: the renowned “Flash” spell. As soon as I unlocked it I quit. I didn’t even play one game with it unlocked. I had shifted my motivation for playing the game to “I want to unlock Flash,” and as soon as I did I found I had no motivation left to play.

Cue 1000 screaming fan boys on how overpowered Flash is and how I should totally play with it.

In both of these cases the games presented me with a goal to work towards that undermined my intrinsic desire to play the game. From a designer’s point of view this is fine, so long as the extrinsic motivations (rewards) remain. So long as I could continue selling items on the Diablo 3 auction house, I would keep playing. Unfortunately, there are two obvious occurrences that take players’ rewards away. The simplest one, exemplified by my League of Legends story, is that the player can achieve the reward. The other problem, as shown in my Diablo 3 anecdote (and many others) is the reward becoming obsolete. Between these two issues it’s difficult for a designer to add fixed reward schedules into a game without risk of the overjustification effect coming into play.

Giving Rewards

Giving rewards in games is desirable. Designers want to give players rewards for numerous reasons, including reinforcing player behavior, increasing players’ feelings of mastery, scaling difficulty over the course of gameplay, and scaffolding mechanics and player abilities. So how can designers give rewards with the perils of triggering overjustification looming overhead and threatening to make their players lose interest in the game? Lepper and Nisbett’s second group of kindergarteners (the group I didn’t reveal the results for) give us a hint at the answer. Recall that this group was the one that were given ribbons after drawing, but were not promised them beforehand. Once the rewards were removed, this group continued to draw at the same rate as group number one.

This gives designers the solution to providing rewards while avoiding shifting players’ motivations to solely wanting rewards! Don’t let the player know for certain that she’s going to get a reward —also known as variable reward schedules. It’s pretty straightforward: when a player knows what she’s going to receive by means of a reward, she can play only for that reward. It’s much harder to make that motivational shift when the reward is uncertain. This is why games like Dota 2 give items as rewards after games fairly infrequently, at (almost) unpredictable times and with random quality: this way players can enjoy the surprise of the reward without banking on it.

Dota 2 gives payoffs when the “battle experience” bar up at the top fills up. I couldn’t for the life of me tell you how many battle points I have, which means it’s as good as random and Valve is doing a great job!

My point here is that not only are variable ratio reward schedules not inherently evil, they are actually good game design practice. Variable ratio reward schedules don’t trick players into playing more than they really want to, they trick the players’ brains to prevent them from shifting their justification for playing to external factors. This means that these reward schedules keep the players playing because they find the experience itself fun and not just to get to the next reward, AND THIS IS EXACTLY WHAT GAME DESIGN IS! Game design is the process of making systems that players find interacting with fun and worthwhile without external justification. Omitting variable ratio rewards when they could be included is just like ignoring other established design theory (say scaffolded learning or positive feed back loops) that we’ve discussed on Most Dangerous Game Design previously: it’s simply shoddy design practice.

Can designers abuse the psychology of reward schedules? Of course! Most of human psychology can be abused and often is. However, even when using psychology, “tricking” players into having more fun still counts as giving players more fun. I know this entire arguments tends to raise peoples’ hackles, so please feel free to argue with us in the comments, as always!

篇目4,Rewarding Difficulty in Game Design: Intrinsic vs. Extrinsic

by Josh Bycer

This year, two very different games released grand changing patches: Diablo 3 and Payday 2. Both were designed around the same purpose of bringing people back to playing with new challenges and rewards. However, while people enjoyed Diablo 3, there has been an outcry over Payday 2 and this brings up the challenge of rewards and difficulty when it comes to game design.

Making the Right Carrot:

Before we talk about rewards, let’s go over the recent changes. Diablo 3 released patch 2.0, bringing the PC version in line with the console in terms of loot balancing as well as getting the game ready for the upcoming expansion. I spent an entire post talking about the Diablo 3′s 2.0 patch on Game-Wisdom. The short version was completely redoing the loot tables to offer gradual improvements as opposed to polarizing ones. And a redesign of the difficulty settings to spread out the challenge instead of making the game too easy or too difficult.

Payday 2 had what Overkill called the Death Wish update. First, there was a redesign across the difficulty levels of how stealth works. Now it is a lot harder, or even impossible on some maps to take out every guard one at a time and have the level to yourself.

But the big change came in the form of the new difficulty, of course titled Death Wish. Death Wish is Payday 2′s version of the original’s infamous Overkill 145 difficulty or expert mode. Here, when you play a level on death wish, the levels feature slight variations such as unbreakable cameras, more obstacles and harder fights.

Harder fights as in enemies spawn more, move faster, aim quicker have more health and damage and there are two new enemies. Elite units with heavy armor and the affectionately titled “Skulldozer”: a heavy unit wielding a light machine gun with heavy damage.

Overkill has also introduced a new challenge: If you can beat every map on each of the difficulty levels, you’ll receive a unique mask for each. But as we mentioned earlier, people are not happy about Payday 2′s changes.

The problem is twofold, one being the intense difficulty increase that was added in the patch and the other is motivation or rewarding the player for taking on the challenge.

The difficulty increase can be a separate topic and one we’re not going to focus too much on here, but rewarding the player.

What it comes down to is that no matter the player, they want to be rewarded for playing a hard game or harder difficulty. Now I know that there are expert players out there getting ready to respond with “But playing a hard game is its own reward for me,” and they are right. However playing a challenging video game does provide an intrinsic reward.

There is a certain thrill with being able to beat something difficult, we see this in games like Ninja Gaiden Black or Dark Souls. But there is a saying that I keep coming back to: It’s easy to make a hard game, but a challenging one is a different matter.

Intrinsic Rewards:

In order for a hard game to be intrinsically rewarding there are several factors that need to be in place. First is that the game has to be fair to the player in the sense that it can’t be needlessly difficult.

Elements like just raising enemy stat values doesn’t change the game, it just means the player is going to have to spend more time grinding or fighting. Ninja Gaiden Black is a great example of making a game harder by actually changing the enemies you would fight based on your difficulty level. Harder enemies reacted quicker, had new attacks and challenged the player differently.

Another no-no is restricting options. In the sense that if you let the player have a variety of skills, power-ups etc, but then say that there is only one or two ways to beat the game on hard mode that doesn’t work. Because you’re making the game less varied at the higher levels and forces the player into a black and white experience of pass or fail unless they do X.

Extrinsic Rewards:

Moving on let’s talk about extrinsic rewards which is a lot easier to discuss. Basically anything that provides some kind of a bonus or award to the player counts as an extrinsic example. So loot, achievements, even a new avatar picture on your profile is an example. Extrinsic rewards don’t all have to be game changing, but they do need to have an impact of some kind.

The most important aspect behind extrinsic rewards compared to intrinsic, is that they need to always be within the player’s grasp. This is where that compulsion to play ARPGs comes from: That your next piece of loot is always around the corner.

You can see the difference in the right and wrong way of extrinsic rewards when comparing Crackdown to GTA in terms of collectibles. In Crackdown, every agility orb provided both a short and long term reward for collecting them.

While in the GTA series, you only received a reward for collecting certain # of special packages or killing pigeons in GTA 4.

So while the former provided constant rewards, the latter only did after the player performed enough tasks with nothing in between. With that said, let’s go back to Payday 2 and Diablo 3 to see where the differences lie.

Measuring the Stick:

Diablo 3′s biggest change from launch to patch 2.0 was how rewards are delivered. Instead of going long periods of time without finding anything good and then getting that one amazing piece, loot is now designed around a gradual and tighter increase in improvement. So you’re going to find better loot quicker and work your way up to that bad-ass level, instead of just getting there all of a sudden.

This is the right way of building an extrinsic reward system as it constantly motivates the player to move forward. Intrinsically, there is the thrill at playing on Diablo 3′s newly redesigned difficulty levels which combines both intrinsic and extrinsic for a great experience.

The problem with Payday 2 at the moment is that neither side is fully developed with the new Death Wish mode. Intrinsically, the higher difficulty doesn’t feel balanced to the skill trees and equipment currently in the game, and requires an almost robotic like method of playing to stand a chance.

Again extrinsically, the promise of a new mask but only after going through all the heists doesn’t really work. A possible alternative for example, beating each heist unlocked something in game like something for the safe house or a specialty mask in of itself, which could provide some motivation along the way towards the big prize.

What’s Better?

For the last point of this piece, I want to touch on the question of what is better: intrinsic or extrinsic value?

This is an interesting point and I feel that this is more about the person rather than the design. For me, I could care less about achievements and more about the challenge involved.

But at the same time, I don’t want to play something that is hard just for the sake of being hard, I want to be challenged with something new and exciting that wouldn’t have been possible on the easier difficulty settings. That doesn’t mean that I don’t like rewards like hats and aesthetic items, but I want them to be attached to a meaningful action.

Understanding how people are motivated to play your game is an important consideration; not everyone wants to play a game for either one or the other. And while having both intrinsic and extrinsic options are great, they need to be paired with a tough but fair difficulty system to truly get the impact right.

篇目5,The Reward series, part 1: The basics of reward

William

This article is the first part of a series about reward in computer games and all that is related to it. In this article, I’ll explore the basics of rewards. First, I define what a reward is. Then, I talk about what rewards mean for the game as a whole and what happens if a game isn’t rewarding enough. After that, I’ll try to identify the different types of rewards a game designer can use and finally, I’ll discuss some ways in which we can make rewards more effective.

Reward

A reward is something you receive and feel positive about. There are three aspect of that definition I believe deserve some explanation: something, receive and feel positive about. And then there is an aspect that is not in the definition and that warrants some explanation because of it. I’ll get to that in a minute,

The term something is vague on purpose. It doesn’t really matter what you receive, as long as you feel positive about it, it’s a reward. It may be something very tangible, like a pouch of coins, or it might be less tangible like a pat on the back or a compliment. It doesn’t matter whether the game designer put it in the game explicitly, nor does it matter whether you are aware of the something. All that matters is that you feel positive about it when you receive it.

The word receive might lead you to believe that I mean that a reward is always given to you, but I don’t. Sure, it might be that someone hands you a healing potion; in that case you received a reward. Or it might be the game that gave you points or some extra time; again, you receive a reward. Or it might be that the developers of the game gave you a worthwhile experience and then that’s the reward you received. But sometimes you just encounter a reward, you just run into it. For example, you see a couple of children playing and it brings a smile to your face. You didn’t really receive that, it wasn’t actually given to you, but it’s still a reward. So, receive might not be the perfect word to use, but it’s the best I could come up with. And we do need a verb in there, because otherwise it isn’t enough; a reward isn’t just something you feel positive about. I feel positive about massages, but unless I actually receive one, it’s not a reward to me. (Giving one might be rewarding too, of course.)

The most important part of the definition is that you feel positive about what you received. I hope that doesn’t need explaining, because I really wouldn’t know how to explain it; it’s just what the word means. I do want to emphasize, though, that we are talking about a feeling here. In other words, what is or is not a reward is completely subjective. If you give me a whack on the head and I say ‘thanks, I really needed that’, then you just gave me a reward. If I repay you in kind, you might be less enthusiastic. The point is that only the one who receives the something can determine whether it’s a reward or not. As game designers we can make an educated guess whether something will be perceived as a reward by the player or not, but we can’t be sure. We might intend for something to be a reward, while it really is not or vice versa: only the player can determine that.

What is missing from the definition is the notion that a reward must be earned. When talking about rewards in (computer) games, I think it is correct to leave this out. Often a reward will be given because the player performed a certain action and yes, in that case the player earned the reward: action = reaction. But that isn’t strictly necessary. If the game is set up to give the player extra money every time a certain random time interval has expires, then the player didn’t really do anything to earn the money, but if she feels positive about receiving it, it’s a reward. (I’m assuming that time elapsed isn’t an important factor in a game, like when playing a turn-based strategy game). It’s likely that most rewards in a game must be earned, but some may not, so earning is not part of the definition. It does have an effect on how the reward might be perceived, though. I’ll discuss that later in this article.

A worthwhile experience

A game must offer what I call a worthwhile experience, otherwise I’m not going to play it. A game must provide an experience that I feel positive about. In other words, a game must be rewarding. The entire reason we decide to play a game, is because we expect to be rewarded for it, to feel that we are having a worthwhile experience.

What exactly that reward is, is of course subjective, but there must be something about the game you enjoy, otherwise you wouldn’t play it. Maybe you play Bejeweled because the sound of falling gems relaxes you. Or maybe you play Quake because killing monsters makes you feel powerful. Or maybe you play Civilization because you enjoy the fantasy of building an empire. Then again, you might prefer to play The Sims because you like the idea that you can take out the trash using nothing but your mouse. Or you might play System Shock because you like being scared shitless. Or maybe you play Paradoxion because it makes you feel smart. Whatever game you play, you play it because you want to get something out of it, something you feel positive about (even if others find it weird).

In order for a game to provide a rewarding experience as a whole, it must contain certain elements that are rewarding. You can’t create a game that constantly kicks me in the shin – something I find extremely annoying – but leaves me feeling that the game as a whole was quite enjoyable. There must be at least something in the game that I would consider a reward, otherwise the game won’t provide me with a worthwhile experience. Of course, that doesn’t mean everything should be a reward, or that nothing can be annoying. After all, I do enjoy a game of football (or soccer, if you prefer) on occasion and that includes a bit of shin kicking, which I’ll just take for granted. But still, for a game to be rewarding, it has to include rewards.

Chores and frustrations

Even a game that offers some rewards might not be rewarding as a whole. One of two things can go wrong. Either the game has too many annoyances or the game has too little rewards. In the first case, playing the game is frustrating and in the second case, playing the game is a chore.

A game is frustrating when it annoys you. Your soldiers keep walking the wrong way, or you’re faced with a puzzle that you just can’t solve, or you lose all the time, or the game is just not supposed to do that! Pound on the keyboard, yell at your friends, throw the controller across the room, it won’t help one bit: the rewards you receive cannot make up anymore for all those things that annoy you about the game. Strangely enough, sometimes we feel compelled to keep playing regardless of the frustration. Maybe it’s because we don’t like the thought of being beaten by a stupid computer game! Or maybe we still hope for that wonderful feeling we had the last time we played this game. Whatever the case may be, there’s really only one thing you should do when a game frustrates you: stop playing it.

Sometimes a game doesn’t annoy you, but you don’t get any rewards either. Such a game is a chore, it’s boring. It’s like ironing your clothes: it isn’t really a punishment, but you don’t feel positive about it either. (No, I’m not saying ironing is a game, it’s just a comparison.) Often, a game becomes a chore when rewards are spread too far apart. You spend endless minutes (or hours, doesn’t really matter since they’re endless anyway) walking around the forest looking for that Magic Chest, but you don’t find anything: no friends, no foes, no chests. Chore, I say. It might also be that what the designer intended as a reward just doesn’t fill you with that positive feeling you are after. I actually felt this way after playing Morrowind for a while. At some point I realised that running errands for some in-game character didn’t feel particularly adventurous anymore. I just did what I did, because I was supposed to do that. I wasn’t playing a hero, I was someone’s whipping boy. (Actually, I was everybody’s whipping boy.) There was too little reward left in the game for me, so I gave it up. Chore: boring.

Types of reward

As game designers, we should be aware of the rewards our games can offer. It helps us to make an educated guess about what players will feel positive about. There are many types of rewards in a game. I’m sure the following list is incomplete, but an incomplete list is better than no list at all, so here goes.

Resource rewards. In games where resources play a role, receiving those resources is often a reward. Resources can be anything: money, food, soldiers, weapons. Including resource rewards in a game is usually not hard to do, because the game requires those resources.

Skill rewards. Some games have explicit systems for letting the player improve. One example is the various skills in role-playing games like strength, stamina and speed. Another example is the technologies in Civilization. Skill rewards give the player a feeling of improvement.

Extension rewards. If a game can end because the player runs out of health or time, then there is room for extension rewards. By giving the player extra health, extra lives or extra time, you extend the time the player can spend on her current game. She’ll consider this a reward, unless of course she already considers your game a chore or a frustration; extension rewards can’t help you out of that one.

Visceral rewards. Graphics, music and sound, when well done, can be very rewarding to the player. Many people enjoy the blood and gore in games like Doom and Carmageddon or the naked ladies in a game of strip poker. A visceral reward doesn’t offer the player anything in terms of the gameplay, but it does enhance the experience.

Accomplishment rewards. When a player accomplishes something in the game that can be a reward by itself: beating an opponent, finishing a level, matching three pink bananas. Accomplishment rewards are tricky, because everyone feels differently about them and what may be an accomplishment to the player in the beginning of the game may just be routine at the end of it.

Motivational rewards. The points a player receives during a game usually have no effect on the gameplay whatsoever, but they do help to motivate the player, to encourage her to score more points. The same goes with that shiny, gold cup with the number one on it you get after winning a race. Cut scenes also fall into this category, although they might offer more than just motivation. An encouraging word from an in-game character might also do the trick.

Of the types of rewards listed above only resource rewards, skill rewards and extension rewards offer the player something in terms of the game itself. Visceral rewards, accomplishment rewards and motivational rewards have no influence on the game itself, but they can add to the experience and thus have an effect on the game as far as the player is concerned. I’ll call the first group gameplay rewards and the second group experience rewards.

Reward intensifiers

Just as important to the game designer as rewards, are the various methods you can use to increase the effectiveness of your rewards. I call these methods reward intensifiers. They don’t add new rewards to the game, but they do make the rewards you receive taste even sweeter, they make you feel more positive about them. Again, the following list is not complete, but it’s better then no list.

Increased benefits. A simple way to intensify a reward is to increase the benefits the player receives from the reward. For gameplay related rewards, this can mean things like more money, more strength or more time. For experience rewards it might mean more blood and gore or more points. (I don’t think you can apply increased benefits to accomplishment rewards.) Increased benefits have only limited effectiveness; there is a point beyond which the player just won’t feel more positive for receiving more benefits. Also, with gameplay rewards increased benefits can upset the balance of the game, so be careful.

Anticipation. If all the characters a player meets during her quest keep talking about that beautiful Magic Gemstone, then it’s likely she wants to find that much sought after item. When she finally does find it, she’s probably going to be very thrilled and tell everyone she is now the owner of the Magic Gemstone. Without the anticipation, she might just pick up the gemstone, put it in her backpack and never give it another thought. Anticipation can also come from outside the game, for example, when all your friends keep talking about that cool cut scene that’s coming up after you beat the Big Annoying Boss.

Accomplishment. Accomplishment can be a reward in itself, but it can also serve to intensify other rewards. When the player just walks into the forest, walks around a bit and then finds the Magic Gemstone, it might not feel very special to her, despite the anticipation. On the other hand, if she has to beat a lot of monster for it, or if she went through great trouble to discover the location of the Magic Gemstone, then she’ll feel a lot better about herself for finding it.

Prize. If you offer a reward as a prize, then that implies that the player has earned the reward. Picking up health packs that are scattered throughout the level often doesn’t feel like receiving a prize, but getting an extra life for finishing the level might. Prizes and accomplishments complement each other nicely. The player already feels rewarded because of her accomplishment and by offering her another reward, making that reward the prize, she’ll surely be left with a positive feeling.

Conclusion

A reward is something you feel positive about. Rewards are essential to a game, if you don’t have enough of them your game may become a chore or even frustrating. If you use rewards just right, though, you create a worthwhile experience. There are many kinds of rewards you can use for your game. Just as important, there are ways to intensify those rewards.

篇目6,Paul Williams is undertaking a PhD in Cognitive Psychology at the University of Newcastle, under the supervision of Dr. Ami Eidels. He is interested in developing online gaming platforms suitable for the investigation of cognitive phenomena, and is currently focused on refining and implementing a novel paradigm to study the behavioral phenomenon known as the “hot hand.”

Balancing Risk and Reward to Develop an Optimal Hot-Hand Game

Abstract

This paper explores the issue of player risk-taking and reward structures in a game designed to investigate the psychological phenomenon known as the ‘hot hand’. The expression ‘hot hand’ originates from the sport of basketball, and the common belief that players who are on a scoring streak are in some way more likely to score on their next shot than their long-term record would suggest. There is a widely held belief that players in many sports demonstrate such streaks in performance; however, a large body of evidence discredits this belief. One explanation for this disparity between beliefs and available data is that players on a successful run are willing to take greater risks due to their growing confidence. We are interested in investigating this possibility by developing a top-down shooter. Such a game has unique requirements, including a well-balanced risk and reward structure that provides equal rewards to players regardless of the tactics they adopt. We describe the iterative development of this top-down shooter, including quantitative analysis of how players adapt their risk taking under varying reward structures. We further discuss the implications of our findings in terms of general principles for game design.

Key Words: risk, reward, hot hand, game design, cognitive, psychology

Introduction

Balancing risk and reward is an important consideration in the design of computer games. A good risk and reward structure can provide a lot of additional entertainment value. It has even been likened to the thrill of gambling (Adams, 2010, p. 23). Of course, if players gamble on a strategy, they assume some odds, some amount of risk, as they do when betting. On winning a bet, a person reasonably expects to receive a reward. As in betting, it is reasonable to expect that greater risks will be compensated by greater rewards. Adams not only states that “A risk must always be accompanied by a reward” (2010, p. 23) but also believes that this is a fundamental rule for designing computer games.

Indeed, many game design books discuss the importance of balancing risk and reward in a game:

* “The reward should match the risk” (Thompson, 2007, p.109).

* “… create dilemmas that are more complex, where the players must weigh the potential outcomes of each move in terms of risks and rewards” (Fullerton, Swain, & Hoffman, 2004, p.275).

* “Giving a player the choice to play it safe for a low reward, or to take a risk for a big reward is a great way to make your game interesting and exciting” (Schell, 2008, p.181).

Risk and reward matter in many other domains, such as stock-market trading and sport. In the stock market, risks and rewards affect choices among investment options. Some investors may favour a risky investment in, say, nano-technology stocks, since the high risk is potentially accompanied by high rewards. Others may be more conservative and invest in solid federal bonds which fluctuate less, and therefore offer less reward, but also offer less risk. In sports, basketball players sometimes take more difficult and hence riskier shots from long distance, because these shots are worth three points rather than two.

Psychologists, cognitive scientists, economists and others are interested in the factors that affect human choices among options varying in their risk-reward structure. However, stock markets and sport arenas are ‘noisy’ environments, making it difficult (for both players and researchers) to isolate the risks and rewards of any given event. Computer games provide an excellent platform for studying, in a well-controlled environment, the effects of risk and reward on players’ behaviour.

We examine risk and reward from both cognitive science and game design perspectives. We believe these two perspectives are complementary. Psychological principles can help inform game design, while appropriately designed games can provide a useful tool for studying psychological phenomena.

Specifically, in the current paper we discuss the iterative, player-centric development (Sotamma, 2007) of a top-down shooter that can be used to investigate the psychological phenomenon known as the ‘hot hand’. Although the focus of this paper is on the process of designing risk-reward structures to suit the design requirements of a hot-hand game, we begin with an overview of this phenomenon and the current state of research. In subsequent sections we describe three stages of game design and development. In our final section we relate our findings back to more general principles of game design.
The Hot Hand

The expression ‘hot hand’ originates from basketball and describes the common belief that players who are on a streak of scoring are more likely to score on their next shot. That is, they are on a hot streak or have the ‘hot hand’. In a survey of 100 basketball fans, 91% believed that players had a better chance of making a shot after hitting their previous two or three shots than after missing their previous few shots (Gilovitch, Vallone, & Tversky, 1985).

While intuitively these beliefs and predictions seem reasonable, seminal research found no evidence for the hot hand in the field-goal shooting data of the 1980-81 Philadelphia 76ers, or the free-throw shooting data of the 1980-81 and 1981-82 Boston Celtics (Gilovitch et al., 1985). With few exceptions, subsequent studies across a range of sports confirm this surprising finding (Bar-Eli, Avugos, & Raab, 2006) – suggesting that hot and cold streaks of performance could be a myth.

However, results of previous hot hand investigations reveal a more complicated picture. Specifically, previous studies suggest that a distinction can be made between tasks of ‘fixed’ difficulty and tasks of ‘variable’ difficulty. A good example of a ‘fixed’ difficulty task is free-throw shooting in basketball. In this type of shooting the distance is kept constant, so each shot has the same difficulty level. In a ‘variable’ difficulty task, such as field shooting during the course of a basketball game, players may adjust their level of risk from shot-to-shot, so the difficulty of the shot varies depending on shooting distance, the amount of defensive pressure, and the overall game situation.

Evidence suggests it is possible for players to get on hot streaks in fixed difficulty tasks such as horseshoe pitching (Smith, 2003), billiards (Adams, 1996), and ten-pin bowling (Dorsey-Palmenter & Smith, 2004). In variable difficulty tasks, however, such as baseball (Albright, 1993), basketball (Gilovitch et al., 1985), and golf (Clark, 2003a, 2003b, 2005), there is no evidence for hot or cold streaks – despite the common belief to the contrary.

The most common explanation for the disparity between popular belief (hot hand exists) and actual data (lack of support for hot hand) is that humans tend to misinterpret patterns in small runs of numbers (Gilovitch et al., 1985). That is, we tend to form patterns based on a cluster of a few events, such as a player scoring three shoots in a row. We then use these patterns to help predict the outcome of the next event, even though there is insufficient information to make this prediction (Tversky & Kahneman, 1974). In relation to basketball shooting, after a run of three successful shots, people would incorrectly believe that the next shot is more likely to be successful than the player’s long term average. This is known as the hot-hand fallacy.

A different explanation for this disparity suggests shooters tend to take greater risks during a run of success, for no loss of accuracy (Smith, 2003). Under this scenario, a player does show an increase in performance during a hot streak – as they are performing a more difficult task at the same level of accuracy. This increase in performance may in turn be reflected in hot hand predictions, however would not be detected by traditional measures of performance. While this hypothetical account receives tentative support by drawing a distinction between fixed and variable difficulty tasks (as the hot hand is more likely to appear in fixed-difficulty tasks, where players cannot engage in a more difficult shot), this hypothesis requires further study.

Unfortunately, trying to gather more data to investigate the hot hand phenomenon from sporting games and contests is fraught with problems of subjectivity. How can one assess the difficulty of a given shot over another in basketball? How can one tell if a player is adopting an approach with more risk?

An excellent way to overcome this problem is to design a computer game of ‘variable’ difficulty tasks that can accurately record changes in player strategies. Such a game can potentially answer a key question relevant to both psychology and game design – how do people (players) respond to a run of success or failure (in a game challenge)?

The development of this game, which we call a ‘hot hand game’, is the focus of this paper. Such a game requires a finely tuned risk and reward structure, and the process of tuning this structure provides a unique empirical insight into players risk taking behaviour. At each stage of development we test the game to measure how players respond to the risk and reward structure. We then analyse these results in terms of player strategy and performance and use this analysis to inform our next stage of design.

This type of design could be characterised as iterative and player-centric (Sotamaa, 2007). While the game design in this instance is simple, due to the precise requirements of the psychological investigation, player testing is more formal than might traditionally be used in game development. Consequently, changes in player strategy can be precisely evaluated. We find that even subtle changes to risk and reward structures impact on player’s risk-taking strategy.
Game Requirements and Basic Design

A hot hand game that addresses how players respond to a run of success or failure has special requirements. First and foremost, the game requires a finely-tuned risk and reward structure. The game must have several (5-7), well-balanced risk levels, so that players are both able and willing to adjust their level of risk in response to success and failure. If, for example, one risk level provides substantially more reward than any other, players will learn this reward structure over time, and be unlikely to change strategy throughout play. We would thus like each risk level to be, for the average player, equally rewarding. In other words, regardless of the level of risk adopted, the player should have about the same chance of obtaining the best score.

The second requirement for an optimal hot hand game is that it allows measurement of players’ strategy after runs of both successes and failures. If people fail most of the time, we will not record enough runs of success. If people succeed most of the time, we will not observe enough runs of failure. Thus, the core challenge needs to provide a probability of success, on average, somewhere in the range of 40-60%.

The game developed to fulfil these requirements was a top-down shooter developed in Flash using Actionscript. While any simple action game based on a physical challenge with hit-miss scoring could be suitably modified for our purposes, a top-down shooter holds several advantages. Firstly, high familiarity with the style means the learning period for players is minimal, supporting our aims of using the game for experimental data collection. Secondly, the simple coding of key difficulty parameters (i.e. target speeds and accelerations) allows the reward structure to be easily and precisely manipulated. Lastly, a ‘shot’ of a top-down shooter is analogous to a ‘shot’ in basketball, with similar outcomes of ‘hit’ and ‘miss’. This forms a clear and identifiable connection between the current experiment and the origins of the hot hand.

In the top-down shooter, the goal of the player is to shoot down as many alien spaceships as possible within some fixed amount of time. This means the number of overall shots made, as well as the number of hits, depend on player performance and strategy. The game screen shows two spaceships, representing an alien and the player-shooter (Figure 1). The simple interface provides feedback about the current number of kills and the time remaining. During the game the player’s spaceship remains stationary at the bottom centre of the screen. Only a single alien spaceship appears at any one time. It moves horizontally back-and-forth across the top of the screen, and bounces back each time it hits the right or left edges. The player shoots at the alien ship by pressing the spacebar. For each new alien ship the player has only a single shot with which to destroy it. If an alien is destroyed the player is rewarded with a kill.

Figure 1: The playing screen.

Each alien craft enters from the top of the screen and randomly moves towards either the left or right edge. It bounces off each side of the screen, moving horizontally and making a total of eight passes before flying off. Initially the alien ship moves swiftly, but it decelerates at a constant rate, moving more slowly after each pass. This game therefore represents a variable difficulty task; a player can elect a desired level of risk as the shooting task becomes less difficult with each pass of the alien.

The risk and reward equation is quite simple for the player. The score for destroying an alien is the same regardless of when the player fires. Since the goal is to destroy as many aliens as possible in the game period, the player would benefit from shooting as quickly as possible; shooting in the early passes rewards the player with both a kill and more time to shoot at subsequent aliens. However, because the alien ship decelerates during each of the eight passes, the earlier a player shoots the less likely this player will hit the target. If a shot is missed, the player incurs a 1.5 second time penalty. That is, the next alien will appear only after a 1.5 second delay which is additional to the interval experienced for an accurate shot.

Stage One–Player Fixation

After self-testing the game, we deployed it so that it could be played online. Five players were recruited via an email circulated to students, family and friends. Players were instructed to shoot down as many aliens as possible within a given time block. They first played a practice level for six minutes before playing the competitive level for 12 minutes. The number of alien ships a player encountered varied depending on the player’s strategy and accuracy. A player could expect to encounter roughly 10 alien ships for every 60 seconds of play. At the completion of the game the player’s response time and accuracy were recorded for each alien ship.

Recall that one of the game requirements was that players take shots across a range of difficulty levels, represented by passes (later passes mean less difficult shots)–this simple test provides evidence that a player is willing to explore the search space and alter her or his risk-taking behaviour throughout the game. Typical results for Players one and two are shown in Figure 2. In general players tended to be very exploratory during the practice level of the game, as indicated by a good spread of shots between alien passes one and eight. During the competitive game time however players tended to invest in a single strategy, as indicated by the large spikes seen in the competition levels of Figure 2. This suggests that players, after an exploratory period, attempted to maximise their score by firing on a single, fixed pass.

Figure 2: Results for two typical players in Stage one of game development. The upper row shows data for Player 1, and the bottom row shows data for Player 2. The left column presents the frequency (%) of shots taken on each pass in the practice level, while the right column indicates the frequency (%) of shots taken on each pass in the competition level. Note that players experimented during the practice level, as evidenced by evenly spread frequencies across passes in the left panels, but then adopted a fixed strategy during the competitive block, as evidenced by spikes at pass 4 (Player 1) and pass 5 (Player 2). For each panel, n is the overall number of shots attempted by the player in that block, m is the mean firing pass, and sd is the standard deviation of the number of attempted shots.

In experimental terms, this fixation on a single strategy is known as ‘investment’. At the end of the game the players reported that, because of the constant level of deceleration, they could always shoot when the alien was at a specific distance from the wall if they stuck to the same pass. Players thus practiced a timing strategy specific to a particular alien pass (i.e., a specific difficulty level). The number of kills per unit time (i.e., the reward) was therefore always highest for that player when shooting at the same pass. In the example graphs (Figure 2), one player ‘invested’ in learning to shoot on pass four, the other, on pass five. This type of investment runs counter to one requirement of a hot-hand game, creating a major design flaw that needed to be fixed in the next iteration.

Stage Two–Encouraging Exploratory Play

The aim of the second stage of design was to overcome the problem of player investment in a single strategy. The proposed solution was to vary the position of the player’s ship so that it no longer appeared in the same location at the centre of the screen but rather was randomly shifted left and right of centre each time a new alien appeared (Figure 3). Thus, on each trial, the shooter’s location was sampled from a uniform distribution of 100 pixels to the left or to the right of the centre. This manipulation was intended to prevent the player from learning a single timing-sequence that was always successful on a single pass (such as always shooting on pass four when the alien was a certain distance from the side of the screen).

Figure 3: The screen in Stage two of game development. The blue rectangle appears here for illustration purposes and indicates the potential range of locations used to randomly position the player’s ship. It did not appear on the actual game screen.

Once again we deployed an online version of the game and recorded data from six players. Players once again played a practice level for six minutes before they played the competitive level for 12 minutes.

The results for all individual players in the competitive game level are shown in Figure 4. Introducing random variation into the players firing position significantly decreased players’ tendency to invest in and fixate on a single pass. This decrease in investment is highlighted by the increase in the variance seen in Figure 4 when compared to Figure 2. Thus, the slight change in gameplay had a significant effect on players’ behaviour, encouraging them to alter their risk-taking strategy throughout the game. Furthermore, this change helps to meet the requirements necessary for hot hand investigation.

Figure 4: Individual player results for the competition level in Stage two testing. Player’s tendency to fire on a single pass in the competition level has been significantly reduced compared to Stage One, as evidenced by the reduction in spikes and, in most cases, increase in variance. For each panel, n is the overall number of shots attempted by the player in that block, m is the mean firing pass, and sd is the standard deviation of the number of attempted shots.

In Figure 5 we present data averaged across all players for both the practice and competition levels. This summary highlights how the game’s reward structure influenced player strategy throughout play. The left column corresponds to the practice level (not shown in Figure 4), while the right column corresponds to the competition level.

Figure 5: Average player results for Stage two. The left column presents the frequency (%) of shots taken on each pass in the practice level, while the right column indicates the frequency (%) of shots taken on each pass in the competition level. For each panel, m is the mean firing pass and n is the overall number of shots attempted by all players in that block. A comparison of mean firing pass for practice and competition levels highlights that as the game progressed, players fired later.

An inspection of Figure 5 highlights the fact that players’ shooting strategy altered in a predictable manner as the game progressed. For example, the mean firing pass for the practice level (m = 5.8) was smaller than that seen in the competition level (m = 6.21). Thus players tended to shoot later in the competition level. This suggests that the reward structure of the game was biased towards firing at later passes, and that as players became familiar with this reward structure they altered their gameplay accordingly.

Given the need to minimise such bias for hot hand investigation, we examined the risk and reward structure on the basis of average player performance. We were particularly interested in the probability of success for each pass, and how this probability translated into our reward system. Recall that firing on later passes takes more time but is also accompanied by a higher likelihood for success. As the aim of the hot hand game is to kill as many aliens as possible within a 12 minute period, both the probability of hits as well as the time taken to achieve these hits are important when considering the reward structure.

We therefore analysed how many kills per 12-minute block the average, hypothetical player would make if he or she were to consistently fire on a specific pass for each and every alien that appeared. For example, given the observed likelihood of success on pass one, how many kills would a player make by shooting only on pass one? How many kills on pass two, and so on. Results of this examination are reported in Figure 6. Figure 6A shows the average number of shots taken by players on each pass of the alien (overall height of bar) along with the average number of hits at each pass (height of yellow part of the bar). Figure 6B uses this data to plot the observed probability of success and shows that the probability for success is higher for later passes. This empirically validates that later passes are in fact ‘easier’ in a psychological sense.

Figure 6: Averaged results and some modelling predictions from Stage two of game development. In Panel A, the frequency (%) of shots attempted on each pass is indicated by the overall height of each bar. The proportion of hits and misses are indicated in yellow and blue. Panel B depicts the average probability of a hit for each pass, given by the number of hits out of overall shot attempts. Based on the empirical results, Panels C and D show the predicted number of successful shots if players were to consistently shoot on only one pass for the entire game (see text for details).

These probabilities allow empirical estimation of the number of total kills likely to be attained by the hypothetical average player if they were to shoot on only one pass for an entire 12 minute block. By plotting the number of total kills expected for each pass number, we produce an optimal strategy curve for the current game, as shown in Figure 6C. The curve is monotonically increasing, indicating that the total number of kills expected of an average player increases as the pass number increases. In other words, players taking less difficult shots are expected to make more hits within each game. The reward structure is clearly biased toward later passes, which validates the change in player strategy (i.e. firing on later passes) as the game progressed. As the players became accustomed to the reward structure, their strategy shifted accordingly to favour later, easier shots.

In game terms it might be considered an exploit to shoot on pass eight. Figure 6C indicates that consistently firing on pass 8 would clearly result in the greatest number of kills, making it the ‘optimal’ strategy for the average player. Given that an exploit of this kind reduces the likelihood of players to fire earlier in response to a run of successful shots, the current design still failed to meet the requirements for our hot hand game.

One simple adjustment to overcome this issue was to reduce the penalty period after an unsuccessful shot. While the current time penalty for a missed shot was set to 1.5 seconds, the ability to vary this penalty allows a deal of flexibility within the reward structure. Given that players make many more shots, and thus many more misses, if they choose to fire on early passes – decreasing the time penalty for a miss substantially increases the relative reward for firing on early passes.

In line with this thinking, Figure 6D shows the predicted number of kills in 12 minutes for the average player if the penalty for missing is reduced from 1.5 seconds to 0.25 seconds. This seemingly small change balances the reward structure so that players are more evenly rewarded, at least for passes three to eight. Estimation of accuracy rate on passes one and two were based on a small number of trials, which makes them problematic for modelling; participants avoided taking early shots, perhaps because the alien was moving too fast for them to intercept. Allowing for players to fire on passes three to eight still provided us with sufficient number of possible strategies for a hot hand investigation.

Stage Three–Balancing Risk and Reward

In stage two of our design we uncovered an exploitation strategy in the risk and reward structure of the game where players could perform optimally by shooting on pass eight of the alien. We suspect this influenced players to fire at later passes of the alien, particularly as the game progressed. Using empirical data to model player performance suggested that reducing the time penalty for a miss to 0.25 seconds would overcome this problem.

A modified version of the game, with a 0.25 seconds penalty after a miss, was made available online and data were recorded from five players. Averaged results show that players shot at roughly the same mean pass of the alien in the practice level and the competitive level (Figure 7). This pattern is in contrast with Figure 4, which highlighted a tendency for players to fire at later passes in the 12 minute competitive level. This data confirms the empirical choice of a 0.25 second penalty, and provides yet another striking example of how subtle changes in reward structure may influence players’ behaviour.

Figure 7: Average player results for Stage three of game development. The left plot presents the frequency (%) of shots attempted on each pass in the practice level, while the right plot indicates the frequency (%) of shots attempted on each pass in the competition level. For each panel, m is the mean firing pass and n is the overall number of shots taken by all players in that block. As indicated by the mean firing pass, under a balanced reward structure players no longer attempted to shoot on later passes as the game progressed.

Recall that we began the development of a hot-hand game with the requirement that for each level of assumed risk the game should be equally rewarding (total number of kills) for the average player. By balancing the reward structure, the design from stage three is now consistent with this requirement for investigating the hot hand.

Finally, we required the game to have an overall level of difficulty such that players would succeed on about 40-60 percent of attempts. Performance within this range would allow us to compare player strategy in response to runs of both success and failure. That is, testing for both hot and cold streaks. As highlighted by Figure 8, the overall probability of success does indeed meet this criteria; the overall probability of success (hits) was 43%. Thus, the game now meets the essential criteria required to investigate the hot hand phenomenon.

Figure 8: Averaged results from the competition level of Stage three of game development. In Panel A, the frequency (%) of shots attempted on each pass is indicated by the overall height of each bar. The proportion of hits and misses are indicated in yellow and blue. Panel B depicts the average probability of success for each pass, given by the number of hits out of overall shot attempts. In Panel B, ps is the overall probability of success (hits).

Discussion

We set out to design a computer game as a tool for studying a fascinating and widely studied psychological phenomenon called the ‘hot hand’ (e.g., Gilovitch, Valone, & Tversky, 1985). For this we needed a game that allowed us to investigate player risk-taking in response to a string of successful or unsuccessful challenges.

We designed a simple top-down shooter game where players had a single shot at an alien spacecraft as it made eight passes across the screen. During the game the player faced this same challenge a number of times. The goal of the game was to kill as many aliens as possible in a set amount of time. The risk in the gameplay reduced on each pass as the alien ship slowed down. Shooting successfully on earlier passes rewarded the player with a kill and made a new alien appear immediately. Missing a shot penalised the player with an additional wait time before the next alien appeared.

As a hot hand game it was required to meet specific risk and reward criteria. Players should explore a range of risk-taking strategies in the game and they should be rewarded in a balanced way commensurate with this risk. We also wanted the game challenge to have an average success rate roughly equal to the failure rate, between 40 and 60 percent so that we could use the game to gather data about player’s behaviour in response to both success and failure.

To achieve our objective we developed the game in an iterative fashion over three stages. At each stage we tested an online version of the game, gathering empirical data and analysing the players’ strategy and performance. In each successive stage of design we then altered the game mechanics so they were balanced in a way that met our specific hot hand requirements. The design changes and their effects are summarised in Table 1.

Table 1. A summary of changes to design in each of the stages and the effect of these changes on meeting the hot hand requirements.

Books on game design tend to prescribe an iterative design process. Iterative processes allow unforseen problems to be addressed in successive stages of design. This is especially important in games where the requirements for the game mechanics are typically only partially known and tend to emerge as the game is built and played. Salen and Zimmerman describe this iterative process as “play-based” design and also emphasise the importance of “playtesting and prototyping” (2004, p. 4). For this purpose successive prototypes of the game are required. Indeed we began with only high-level requirements and used this same iterative, prototyping approach to refine our gameplay.

The main difference in our approach is that we more formally measured player’s strategies and exploration behaviours in each stage of design. Given that our game requirements are rather unique, it is unlikely that subjective feedback alone would have allowed us to make the required subtle changes to game mechanics. For example, during the initial testing of the game we found that players tended to invest in a single playing strategy. Further analysis also revealed a potential exploit in the game as players could easily optimise their total number of kills by shooting on the last pass of each alien ship.

The issue of exploits in games is often debated in gaming circles and is also well studied in psychology. Indeed trade-offs between exploitation and exploration exist in many domains (e.g., Hills, Todd, & Goldstone, 2008; Walsh, 1996). External and internal conditions determine which strategy the organism, or the player, will take in order to maximise gains and minimise loses. For example, when foraging for food, the distribution of resources matters. Clumped resources lead to a focused search in the nearby vicinity where they are abundant (exploitation), whereas diffused resources lead to broader exploration of the search space.

Hills et al. showed that exploration and exploitation strategies compete in mental spaces as well, depending on the reward for desired information and the toll incurred by search time for exploration. In the context of our game, a shooting strategy of consistently attempting the easiest shooting level produced the highest reward. This encouraged players to drift toward later firing as the game progressed, and in turn inhibited players from exploring alternate (earlier firing) strategies. It is unlikely we could have predicted this without collecting empirical data from players.

A further advantage of gathering empirical data was that it allowed us to remodel our reward structure based on precise measures of player performance. In stages one and two players lost 1.5 seconds each time they missed an alien. In stage three we reduced this penalty to 0.25 seconds based on our analysis and modelling of player behaviour. This relatively minor change was enough to change players’ behaviour and encourage them to risk earlier shots at the alien. The fact that our game is quite simple in nature reinforces both the difficulty and importance of designing a well-balanced risk and reward structure.

Another common principle referred to in game literature is player-centred design which is defined by Adams as “a philosophy of design in which the designer envisions a representative player of a game the designer wants to create.” (2010, p. 30). Although player-centred design is often a common principle referred to in game-design texts there is some suggestion that design is often based purely on designer experience (Sotamaa, 2007). Involving players in the design process typically involve more subjective feedback from approaches such as focus groups and interviews which have been generally used in usability design. In our study, when designing even a simple game challenge it is clear that the use of empirical data to measure how players approach the game and how they perform can be another vital element in balancing the gameplay.

We also recognise some dangers with this approach, as averaging player performance can hide important differences between players. It would be nice to have a model of an ideal player but it is unlikely such a player exists. In fact there are many different opinions about who the ‘player’ is (Sotamaa, 2007). The empirical data therefore need to be gathered from the available players’ population. If there are broad differences among these players then it may require the designer to sample different groups, for example, a group of casual players and a group of hard-core gamers.

Importantly for future research, the game design at which we arrived is now suitable to investigate the hot hand phenomena. Such a game can potentially answer a number of questions:

1. How do players respond to a run of success or failure in a game challenge?

2. Will a player take on more difficult challenges if they are on a hot streak?

3. Will they lower their risk if they are on a cold streak?

4. How will this variable risk level impact on their overall measure of performance?

5. How can the hot hand principle be used in the design of game mechanics?

Answers to such questions will not only be of interest to psychologists, but could also further inform game design. For example, it might allow the designer to engineer a hot streak so that players would take more risks or be more explorative in their strategies. Of course in a game it might even be appropriate to use a cold streak to discourage a player’s current strategy. The game mechanics could help engineer these streaks in a very transparent way without breaking player immersion. Further investigations of the hot hand hold significant promise for both psychology and game design.


上一篇:

下一篇: