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阐述行为主义心理学对游戏设计的指导作用

发布时间:2011-08-22 15:52:34 Tags:,,,,

作者:John Hopson

每款电脑游戏的设计都围绕着相同的核心因素:玩家。尽管游戏所需的硬件和软件可能发生改变,但是玩家如何学习以及对游戏作出反应的心理学是恒久不变的。对思维的研究确实得出了某些可能改变游戏设计的结果,但这些结果大部分都发表在科学杂志和其他设计师无法接触到的领域。具有讽刺意味的是,许多此类发现均以简单的电脑游戏作为工具来探索人们在不同条件在如何学习和做出动作。

在这片文章中,我要讨论的技术属于行为主义心理学的范畴。该领域的工作和调查通常在动物身上开展,行为主义心理学关注的是实验和能够观察到的动作。行为主义研究的标志之一是,多数主要的实验发现来源于各个物种,其覆盖范围包括鸟类、鱼类和人类等物种。行为主义心理学家寻找的是(游戏邦注:也就是这篇文章关注的焦点)学习的普遍规则以及思维在特定环境下如何做出反应。由于这些规则与物种和环境并无相关,所以它们可用于诸如电脑游戏设计等新颖的领域。与强调玩家应当如何对某种情况做出反应的游戏理论不同的是,这篇文章关注的是玩家会如何应对某种常规环境。

本文提供的并非是让游戏更加完美的方法,阐述的是某些人们对不同类型奖励做出反应的基本知识。每款电脑游戏都会让玩家以某种方式做出反应。心理学可以提供一种框架和术语,让我们可以理解自己正在告诉玩家什么内容。

偶发和计划

偶发是一个或一套管理何时给予奖励的规则。这个发现颇具趣味性,来源于某天B. F. Skinner在实验中给老鼠提供食物球。那天他较为空闲,便开始给老鼠提供食物球,老鼠按压杠杆10次可以得到1个球(游戏邦注:原先是每次按压刚刚都可以得到食物球)。实验过不同的奖励规则之后,他发现各种规则可以引发类型有显著差异的反应。一个全新的心理学领域由此诞生了,而这对游戏设计能起到很强大的作用。

电脑游戏中的偶发更为复杂,但是类似的做法也已经足够。比如,玩家在RPG游戏中赚取经验值来升级或收集奖励道具来获得额外的生命值。在街机类型的游戏中,力量变强似乎是随机性的,或者只有当满足某种条件才能出现。在任何偶发事件中,都需要参与者做出行动才能够获得在某种特定情况下的奖励。这并不是说玩家与老鼠完全相同,但是这些学习规则却通用于这两个物种。

比率和间隔

从本质上来说,偶发包括两种基本类型:比率和间隔。比率计划是在玩家完成特定数量的动作后提供奖励。比如,玩家杀死20个敌人后可以获得额外的生命。这可以称为“固定比率”计划,因为每次奖励所需的杀戮数量是相同的。其他类型的比率将在下文中讨论。

固定比率计划是游戏中最为普遍的偶发之一,通常可以制造出很独特的感觉。首先是个漫长的停顿,然后玩家会尽快地做出动作直到获得奖励。当玩家认为首个动作无法带来奖励并因此没有动力做出首次杀戮时,这种方法就可以发挥作用。一旦参与者决定继续向前,他们会尽快做出动作来快速地获得奖励。

固定比率计划下存在的明显的停顿可能成为游戏设计师的一大问题。那段时间中玩家几乎没有玩游戏的动机,这就很可能导致玩家离开游戏。而且,停顿时间的长短受比率的影响(游戏邦注:即所需动作的数量)。因而,更多动作就需要更长的停顿时间。这意味着如果比率随时间增加,比如在《龙与地下城》中每次升级所需的经验值逐渐增加,那么停顿的时间也会随之增加。最后,停顿变得无穷无尽,玩家会认为等待如此长的时间没有必要,就会离开游戏。

在任何偶发事件中,都会有一些动作会在特定情况下提供奖励(from gamasutra)

在任何偶发事件中,都会有一些动作会在特定情况下提供奖励(from gamasutra)

如此设计的好处在于,在停顿期间,玩家可能会选择不优先去做奖励性行为。比如,如果玩家知道升级需要很长的时间,那么他们可能就会利用这段时间来测试新战术或尝试游戏其他方面的内容。

还有一种是“可变比率”计划,奖励的获得也需要特定数量的动作,但是这个数量每次都会改变。玩家可能需要射落将近20架敌军战机来获得奖励船只,但是每次这个数量都是随机生成的。重点在于必须注意到,玩家不知道这次需要做出多少次的动作,只能从之前的经历中得出平均数字。

在可变比率计划下,参与者通常会以相当高的频率以稳定的动作流程来做出反应。尽管这个频率没有像固定比率计划那么高,但是更为稳定而且没有可能导致问题的停顿。因为有可能玩家击落一架敌军战机就能够增加一次生命(游戏邦注:虽然这种可能性较小),所以玩家总是有战斗的理由。

杀死对手以换取经验值和获得升级就是一种偶发比率(from gamasutra)

杀死对手以换取经验值和获得升级就是一种偶发比率(from gamasutra)

通常来说,可变比率计划能够产生我在这篇文章中讨论的所有计划中最高的整体活动率。这并不意味着它是最棒的方法,但是如果你正在寻找的是高且稳定的比率,那么可变比率偶发正是你所需要的东西。

与之前所述相对的是间隔计划。间隔计划并非根据动作的数量来提供奖励,而是根据经过的时间来提供奖励。在“固定间隔”计划中,一段时间过后的首次动作可以产生奖励。比如,游戏可能会每隔30分钟时间出现增强能力的道具。

对于固定间隔偶发,参与者通常的反应方式是获得奖励后暂停一段时间,然后渐渐越来越快地做出反应知道获得奖励。在上述能力增强道具的例子中,玩家会将注意力集中在游戏其他部分,随后回到场景中看看是否出现新的能力增强道具。如果还没有出现,那么玩家又会将注意力转移到别处。随着奖励的时间逐渐靠近,这种查看将变得越来越频繁。靠近奖励时间时,玩家会坐在那里等待获得奖励。

和固定比率系统的是,这里也存在可能给游戏设计师带来问题的停顿。与固定比率不同的是,并没有始终保持高活动率,活动率会随着时间的临近逐渐增加。但是停顿这个令玩家失去动机的阶段仍然存在。

当然,也有“可变间隔”计划,每次奖励后所间隔的时间是变化的。它类似于可变比率计划,也能够产生稳定和持续性的活动水平,虽然节奏会比较缓慢。如同可变比率计划,这里也总是有活动的理由。以之前提到的能力增强道具为例,可能在收集之后马上再次出现,也可能在1个小时之后出现。动机随时间逐渐分散,所以不存在玩家的注意力转移的时间。活动率比可变比率计划要低,因为奖励的出现与活动并无联系。即便玩家在间隔时间内寻找能力增强道具上千次,它的出现也不会变得更快。实验表明,我们很善于分辨出哪些结果源于我们自己的动作,哪些结果与我们的动作无关。

这些是基本的构建模块,但并非只有这些方法。每种偶发都是对时间、活动和奖励的安排,而且也有无数种将这些元素捆绑以创造你需要玩家做出的活动样式的方法。

特殊情况

在偶发的研究中,有些许特殊情况需要引起特别的注意。首先是“链计划”,即偶发中存在多个阶段的情况。比如,玩家可能需要杀死10个半兽人才能够进入龙穴,但是龙的出现可能是随机的。这些计划通常出现在多阶段解谜和RPG任务中,人们通常以某种非常特别的方法做出反应:他们将进入计划的下个阶段本身视为奖励。就像刚刚提到的例子那样,多数玩家会将第一部分视为固定比率计划,而将后续的可变间隔计划视为奖励。

其次是所谓的“灭绝”,即当你停止提供计划时会发生什么事情的问题。假如玩家乐于在龙每次出现时对其进行屠杀,但是屠杀特定数量之后龙就不再出现。那么玩家会怎么做呢?答案就是,偶发终结之后的行为取决于偶发本身。在比率计划中,玩家会继续在长期时间内保持较高的行动率,然后逐渐停止此类行动。在固定间隔计划中,他们的活动会逐渐达到顶峰,因为他们期望能够在间隔后获得奖励,之后会逐渐停止活动。

灭绝包含大量的挫败感和愤怒,这是种普遍规则。我们期待自己的活动能够持续有意义,当偶发发生改变时,我们会感到很愤怒。有趣的是,这种情况并非只出现在人类身上。在某个时间中,将两只鸽子关在笼子中。一只鸽子被锁在笼子上,另一只可以自由行动。每隔30秒时间,加料斗中会出现少量的食物(游戏邦注:即固定间隔计划)。自由的鸽子能够吃到食物,但是那只被拴住的鸽子无法吃到,所以自由的鸽子每次都很开心地吃掉所有的食物。一个小时左右后,加料斗停止供应食物。在一段时间内,自由的鸽子会继续每隔30秒时间查看加料斗,但是当它明白食物不会再出现时,它会飞到笼子那头去攻击另一只鸽子。有趣的是,那只被拴住的鸽子从未吃过食物,随意自由的鸽子根本没有理由去责怪它必须为食物停止供应而负责。尽管这种挫败感是毫无理性的,但事实就是如此。

有种相关现象称为“行为反差”,发生在黑猩猩以及其他物种间。黑猩猩做出拉杠杆之类简单的动作就可以获得生菜作为奖励。过段时间后,将每次拉杠杆的奖励变为它们更喜欢吃的葡萄。接下来,黑猩猩有次拉杠杆后又得到了生菜,它们会变得很愤怒,将生菜抛向实验人员。之前它们为自己得到生菜感到欣喜,但是葡萄的出现给了它们新的期待,当这些期待没有得到满足时,挫败感和愤怒就会产生。

从上述例子可以得出的结论是,减少加强的水平对玩家来说是种惩罚,并且可能导致他们离开游戏。此类做法必须谨慎且循序渐进,否者就有可能带来难以预料的影响。甚至连暂时的削减也可能出现这种情况,比如当杀死半兽人不再提供经验值而且玩家还未发现可以转而屠杀巨魔来获得经验值。瞬间的奖励丧失令人感到极为厌恶,如果可能的话,应该尽量避免。

最后一种特殊情况是所谓的“回避”,即参与者做出行动来避免某些事情发生的偶发。相关的简单实验是将老鼠关在有个小杠杆的笼子中。笼子的金属门上不时会有小电击(游戏邦注:电击的频率是随机的)。但是,如果老鼠按压杠杆,那么至少在30秒内电击不会发生。老鼠很快便学会了以稳定的频率来按压杠杆,从而防止电击的发生。

老鼠很快便学会了以稳定的频率来按压杠杆以避免电击(from gamasutra)

老鼠很快便学会了以稳定的频率来按压杠杆以避免电击(from gamasutra)

我所知道的最佳的游戏例证是《Ultima Online》,玩家需要定期访问他们的城堡或房屋,否则这些建筑物便会开始逐渐衰败。正如上文中提到的实验室实验一样,有参与者会努力保持事情不发生,维持现状。从游戏开发者的角度来看,这是种相对较为廉价的战略,因为他们不用不断给玩家提供新玩具或奖励。

逾50年时间以来,偶发都是心理学的主要工具,因而存在各种特殊情况和独特计划。以上是需要引起游戏开发者注意的三种特殊情况。

诀窍

为使之前所讨论的想法更容易理解,我将阐述些许使用哪种偶发来实现特定效果的原则。这些并非解决此类为题的唯一方法,但是它们简单、可靠且非常有效。

如何让玩家在游戏中投入精力。转变成我们通常使用的说法,就是我们要如何让玩家持续性地维持高活动率?看看我们说过的4个基本计划,可以得出可变比率计划这个答案,玩家的每个反应都有可能创造奖励。活动水平衡量的参与者期望奖励在多长时间内会出现的度量。他们越确定有些很棒或有趣的事情即将发生,他们就越会在游戏中投入精力。当玩家知道奖励还需要很长时间才能获得,比如当玩家刚刚升级并且需要数千点经验值才能再次升级,他们的驱动力和活动就会降低。

如何让玩家不断玩游戏。这个问题的答案很简单,即总是赋予玩家玩游戏的理由。上文阐述过的可变计划能够产生持续性的奖励可能性,因而玩家总是有理由去做下一件事情。游戏设计师需要从玩家处获取的是大量“行为惯性”,即保持做他们正在做的事情的趋势,即便在这个过程中不存在直接奖励。可产生大量惯性的计划是回避计划,玩家会努力防止不良事情的发生。即便游戏没有发生进展,玩家也可以通过推迟消极结果的出现来实现某些积极的目标。

如何防止玩家退出游戏。换句话说,玩家会在哪些情况下停止玩游戏,你要如何避免这些情况的出现?我已经说过玩家会停止玩游戏的两种主要情况。其一是停顿,他们在此期间做下一件事情的驱动力很低。驱动力是相对的,玩家玩游戏的愿望总是通过与其他活动的对比来衡量。当他们玩游戏的总体驱动力较高时,他们在游戏中会有极大的愿景去做某件事情,而不会将注意力转移到其他事情上。如果他们刚刚升级并且知道他们需要再过几个小时才能再看到某些有趣事情的发生,相对于其他他们可以做的事情来说,他们玩游戏的驱动力就会相对较低。

解决这个问题的方法之一是在任何时刻提供多个可供选择的活动。这意味着即便杀死怪物无法获得奖励,游戏中还有其他的活动可供玩家选择。如果杀死怪物毫无用处,或许去探索会更好。玩家可以花些时间去改善他们的装备或练习新战术。应该注意的是,这种主要活动驱动力的下降可以使得次要活动的驱动力上升。在这个例子中,次要活动也是游戏的部分内容,重新引导玩家在游戏中的注意力并防止他们退出游戏。

另一个可能导致玩家退出游戏的情况是我之前在大猩猩例子中提及的奖励迅速下滑。与驱动力一样,奖励也是相对的。与之前所获得奖励价值的对比才能够体现出当前奖励的价值。如果当前奖励的价值较低,玩家会觉得有挫败感或感到愤怒。这种对期盼的冒犯会被当成是种挑衅行为,是游戏创造者的不公平决定。尽管游戏可以随时间逐渐增加难度,但是最好避免奖励价值的剧烈改变。这对解谜游戏特别有用,因为玩家可能需要在某个问题上花数个小时的时间。如果当前问题的难度比之前谜题有了很大的提升,那么玩家可能就会离开游戏。

结论

将普遍规则用于具体实例中总是间复杂的事情,尤其是在同时存在多种类型的偶发的情况中。多数行为主义心理学实验都是为了表明单个现象,就像X射线可以照射出手臂的骨头那样。皮肤、肌肉等等都没有出现,所以最终得到的结果图片是不完整的。但是即便只有骨头,我们仍然可以猜想出手臂的作用、局限性和灵活程度。这篇文章中讨论的行为主义原则也同样有益处及其局限性。影响玩家心理的因素还有很多,但是结果的基本样式和奖励组成了主要框架。理解潜藏于玩家对我们对其要求的反应的基本样式,我们可以针对目标玩家来设计游戏。

游戏邦注:本文发稿于2001年4月27日,所涉时间、事件和数据均以此为准。(本文为游戏邦/gamerboom.com编译,如需转载请联系:游戏邦

Behavioral Game Design

John Hopson

Every computer game is designed around the same central element: the player. While the hardware and software for games may change, the psychology underlying how players learn and react to the game is a constant. The study of the mind has actually come up with quite a few findings that can inform game design, but most of these have been published in scientific journals and other esoteric formats inaccessible to designers. Ironically, many of these discoveries used simple computer games as tools to explore how people learn and act under different conditions.

The techniques that I’ll discuss in this article generally fall under the heading of behavioral psychology. Best known for the work done on animals in the field, behavioral psychology focuses on experiments and observable actions. One hallmark of behavioral research is that most of the major experimental discoveries are species-independent and can be found in anything from birds to fish to humans. What behavioral psychologists look for (and what will be our focus here) are general “rules” for learning and for how minds respond to their environment. Because of the species- and context-free nature of these rules, they can easily be applied to novel domains such as computer game design. Unlike game theory, which stresses how a player should react to a situation, this article will focus on how they really do react to certain stereotypical conditions.

What is being offered here is not a blueprint for perfect games, it is a primer to some of the basic ways people react to different patterns of rewards. Every computer game is implicitly asking its players to react in certain ways. Psychology can offer a framework and a vocabulary for understanding what we are already telling our players.

Contingencies and Schedules

The concrete translation of “What are we asking of our players?” is “What are our contingencies?” A contingency is a rule or set of rules governing when rewards are given out. The anecdote about this discovery (as passed to me by one of his students) is that one day B. F. Skinner ran low on the small food pellets he gave the rats in his experiments. Rather than risk running out and having to stop work for the day, he began to provide the pellets every tenth time the rats pressed the lever instead of every time. Experimenting with different regimens of reward, he found that they produced markedly different patterns of response. From this was born a new area of psychology, and one that has some strong implications for game design.

The contingencies in computer games are more complex, but the analogy is clear enough. For example, players in an RPG earn experience points to gain levels or collect bonus items to gain extra lives. In an arcade-style game, power-ups appear at random intervals, or only when certain conditions are met. As in any contingency, there are actions on the part of the participant which provide a reward under specific circumstances. This is not to say that players are the same as rats, but that there are general rules of learning which apply equally to both.

Ratios and Intervals

There are essentially two fundamental sorts of contingencies, ratios and intervals. Ratio schedules provide rewards after a certain number of actions have been completed. For example, a player might gain an extra life after killing 20 opponents. This would be called a “fixed ratio” schedule, because the same number of kills is required every time. Other types of ratios will be discussed later.

One of the most common contingencies found in games, fixed ratio schedules typically produce a very distinct pattern in the participant. First there is a long pause, then a steady burst of activity as fast as possible until a reward is given. This makes sense when one considers that the very first action never brings a reward, so there is little incentive to make that first kill. Once participants decide to go for the reward, they act as fast as they can to bring the reward quickly.

The distinct pause shown under a fixed ratio schedule can be a real issue for game designers. Having a period of time where there is little incentive to play the game can lead to the player walking away. Additionally, the length of the pause is a function of the size of the ratio (the number of actions required), so the more actions required the longer the pause. This means that if the ratio increases over time, such as the increasing number of experience points required to gain a level in Dungeons & Dragons, so does the pause. Eventually, the pause can become infinite, and the player simply decides it’s not worth it and walks away.

On the plus side, during the pause other, less rewarding activities often come to the fore. For example, if players know it will take them a long time to gain their next level, they might take the time to test a new tactic or try out different aspects of the game.

There are also “variable ratio” schedules, in which a specific number of actions are required, but that number changes every time. A player might be required to shoot down approximately 20 enemy fighters to gain an extra ship, but the precise number is randomly generated each time. It’s important to note that the player does not know how many actions are required this time, just the average number from previous experience.

Under variable ratio schedules, participants typically respond with a steady flow of activity at a reasonably high rate. While not quite as high a rate as the burst under a fixed ratio schedule, it is more consistent and lacks the pausing that can cause trouble. Since it’s possible (though unlikely) that the player can gain a life for shooting down only one enemy, there’s always a reason to go hunting.

In general, variable ratio schedules produce the highest overall rates of activity of all the schedules that I’ll discuss here. This doesn’t necessarily mean they’re the best, but if what you’re looking for is a high and constant rate of play, you want a variable ratio contingency.

On the other side of the coin there are interval schedules. Instead of providing a reward after a certain number of actions, interval schedules provide a reward after a certain amount of time has passed. In a “fixed interval” schedule, the first response after a set period of time produces a reward. For example, the game might introduce a power-up into the playing field 30 minutes after the player collected the last one.

Participants usually respond to fixed interval contingencies by pausing for a while after a reward and then gradually responding faster and faster until another reward is given. In our power-up example, the player would concentrate on other parts of the game and return later to see if the new power-up had appeared. If it hadn’t, the player would wander off again. Gradually the checks would become more frequent as the proper time approached, until at about the right time the player is sitting there waiting for it.

As in the fixed ratio, there is a pause that can cause problems for a game designer. Unlike the fixed ratio, there is no sharp transition to a high rate of activity. Instead, there is gradual increase as the appropriate time approaches. The pause remains, a period where player motivation is low.

There are also “variable interval” schedules, where the period of time involved changes after each reward. A counterpart to the variable ratio schedules, these also produce a steady, continuous level of activity, although at a slower pace. As in the variable ratio schedule, there is always a reason to be active. The power-up mentioned in the earlier example could reappear immediately after being collected or an hour later. The motivation is evenly spread out over time, so there are no low points where the players’ attention might wander. The activity is lower than in a variable ratio schedule because the appearance is not dependent on activity. If the player looks for the power-up 1,000 times during the interval, it will appear no faster. Experiments have shown that we are very good at determining which consequences are the results of our own actions and which are not.

These are the basic building blocks, but this is by no means an exhaustive list. Each contingency is an arrangement of time, activity, and reward, and there are an infinite number of ways these elements can be combined to produce the pattern of activity you want from your players.

Special Cases

There are a few special cases in the study of contingencies that deserve special mention. First, there are “chain schedules,” situations where there are multiple stages to the contingency. For example, players may have to kill 10 orcs before they can enter the dragon’s cave, but the dragon may appear there at random points in time. These schedules are most commonly found in multi-stage puzzles and RPG quests, and people usually respond to them in a very specific way: they treat access to the next stage of the schedule as a reward in itself. In the example just mentioned, most players would treat the first part as a fixed ratio schedule, the reward being access to the subsequent variable interval schedule.

Secondly, there is the question of what happens when you stop providing a reward, which is referred to as “extinction.” Say the player is happily slaying the dragon every time it appears, but after a certain number of kills it no longer appears. What will the player do? The answer is that behavior after the end of a contingency is shaped by what the contingency was. In a ratio schedule, the player will continue to work at a high rate for a long period of time before gradually trailing off. In a fixed interval schedule, their activity will continue to peak at about the time they expect to be rewarded for a few intervals before ceasing.

As a general rule, extinction involves a lot of frustration and anger on the part of the subject. We expect the universe to make sense, to be consistent, and when the contingencies change we get testy. Interestingly, this is not unique to humans. In one experiment, two pigeons were placed in a cage. One of them was tethered to the back of the cage while the other was free to run about as it wished. Every 30 seconds, a hopper would provide a small amount of food (a fixed interval schedule, as described earlier). The free pigeon could reach the food but the tethered one could not, and the free pigeon happily ate all the food every time. After an hour or so of this, the hopper stops providing food. The free pigeon continues to check the hopper every 30 seconds for a while, but when it’s clear that the food isn’t coming, it will go to the back of the cage and beat up the other pigeon. Now, the interesting thing is that the tethered pigeon has never eaten the food and the free pigeon has no reason to think the other is responsible for the food stopping. The frustration is irrational, but real nonetheless.

A related phenomenon, called “behavioral contrast,” occurs in chimpanzees, among other species. A chimpanzee is doing a simple task such as pulling a lever and is being rewarded with pieces of lettuce, which they like to eat. After doing this for a while, one pull is rewarded with a grape, which they really love to eat. On the next pull, the chimp is given lettuce again and they get very upset, throwing the lettuce at the experimenter. They were perfectly happy with lettuce before, but the presentation of the grape creates new expectations and when those expectations aren’t met, frustration and anger invariably results.

The moral here is that reducing the level of reinforcement is a very punishing thing for your players and can act as an impetus for them to quit the game. It needs to be done carefully and gradually, or there may be an undesirable backlash. This applies even to temporary reductions, such as when killing orcs stops producing points but the player has not yet discovered that trolls can be killed instead. Sudden loss of reward is very aversive and should be avoided when possible.

A final special case that bears mentioning is what is called “avoidance,” contingencies where the participants work to keep things from happening. A simple laboratory example involves a rat in a cage with a small lever. Every so often, a small shock (on the order of a static discharge from a walking across a carpet) is given through the metal floor of the cage. However, if the rat presses the lever, the shock won’t happen for at least 30 seconds. The rat quickly learns to press the lever at a slow, steady rate and thus prevent the shock from occurring.

The best game example of this I know of is in Ultima Online, where players who own castles or houses are required to visit them regularly or they’ll start to decay. As in the laboratory example above, you have participants who are working to keep things from happening, to maintain the status quo. This is a relatively cheap strategy from the point of view of game developers, since they don’t have to keep providing the player with new toys or rewards.

Contingencies have been a major tool in psychology for more than 50 years, so there are a wide variety of special cases and unusual schedules. These three are just a sample of some special cases that are particularly applicable to game developers.

Recipes

To help drive home the ideas I’ve discussed, here are some simple formulas of what contingencies to use to achieve specific results. These are not the only ways to solve these problems, but they are simple, reliable, and very effective.

How to make players play hard. Translated into the language we’ve been using, how do we make players maintain a high, consistent rate of activity? Looking at our four basic schedules, the answer is a variable ratio schedule, one where each response has a chance of producing a reward. Activity level is a function of how soon the participant expects a reward to occur. The more certain they are that something good or interesting will happen soon, the harder they’ll play. When the player knows the reward is a long way off, such as when the player has just leveled and needs thousands of points before they can do it again, motivation is low and so is player activity.

How to make players play forever. The short answer is to make sure that there is always, always a reason for the player to be playing. The variable schedules I discussed produce a constant probability of reward, and thus the player always has a reason to do the next thing. What a game designer also wants from players is a lot of “behavioral momentum,” a tendency to keep doing what they’re doing even during the parts where there isn’t an immediate reward. One schedule that produces a lot of momentum is the avoidance schedule, where the players work to prevent bad things from happening. Even when there’s nothing going on, the player can achieve something positive by postponing a negative consequence.

How to make players quit. In other words, under what circumstances do players stop playing, and how can you avoid them? I’ve discussed two main conditions under which players will stop playing. The first is pausing, where their motivation to do the next thing is low. Motivation is relative: the desire to play your game is always being measured against other activities. While they may have a high overall motivation to play your game, during play they’re comparing their motivation to do the very next thing in the game to all the other next things they could be doing. If they’ve just gone up a level and know that they have an hour of play before anything interesting happens, their motivation will be low relative to all the other activities they could be doing.
One way around this problem is to have multiple activities possible at any given time. This means that even if killing monsters becomes unrewarding, there are other activities within the game that can take up the slack. If monsters are unprofitable, exploration may be better. The player could take some time to improve their equipment or to practice a new tactic. Note that this is the same phenomenon that led to quitting before, a drop in motivation in the main activity raising the motivation of lesser activities. In this case, the lesser activities are also part of the game, redirecting their attention within the game and maintaining a high level of play.

The other situation that can lead to quitting is the sharp drop in rate of reward which I discussed in the chimpanzee example. Just like motivation, reward is relative. The value of the current reward is compared to the value of the previous rewards. If the current reward is 10 times the last one, it will have a big impact on the participant. If the current reward is weaker than experience has led them to believe, the player will experience frustration and anger. Violation of expectations is perceived as an aggressive act, an unfair decision by the game’s creators. While the game can get more difficult over time, it’s best to avoid sharp changes in the rate of reward. This is particularly applicable to puzzle games, where the player may have to spend hours on the same problem before moving on to the next. If the current problem is sharply more difficult than previous puzzles, the player may simply walk away.

Conclusion

The application of general rules to a specific case is always tricky, especially in situations where there is more than one type of contingency operating. Most experiments in behavioral psychology are designed to illuminate a single phenomenon, like an X-ray revealing the bones of an arm. The skin, muscles, and so on aren’t shown, so the resulting picture is incomplete. But even with just the bones, we can make a good guess about how the arm works, its limitations and flexibilities. The behavioral principles discussed here should be understood to have similar benefits and limitations. There are numerous other things that influence players, but the basic patterns of consequences and rewards form the framework which enable all the rest. By understanding the fundamental patterns that underlie how players respond to what we ask of them, we can design games to bring out the kind of player we want. (Source: Gamasutra)


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