作者：Nils Pihl

游戏领域的一大有趣现象是，玩家总会对游戏设计产生影响。无论该游戏模式是否复杂，游戏总为我们的创意输入预留了空间。我们可以增添新规则、新场景、新故事、以及新型的制胜策略，我们可以选择互动的原创特质。在此，游戏更像一本书籍，我们总能从作者引导的字里行间中发现游戏的最有趣部分。

这对游戏设计而言是把双刃剑。玩家在游戏环境中的行为会极大地影响游戏的趣味性，游戏设计师常纠结于如何鼓励玩家采取有利举措。控制玩家的期望与行为是个艰巨但又十分重要的任务。而不太健全的游戏文化领域仍旧缺乏出色的游戏。只有通过玩家，游戏才会演变出优秀本质。

那么，玩家是如何掌控，或参与游戏？他们在游戏中的行为又会如何？为理解这一点，我们首先应理解行为的基本定义。

行为是指人们对特定环境或刺激因素作出的反应。在此，重要的是，我们不能混淆行为的概念，行为是通过动作来描述某人行动的模式。

比如，“我打算去睡觉”便典型地指出这是一个动作，“我将在看完这个电视节目后睡觉，即使我现在很累”则体现出一种行为。动作可以用数据点指代，行为则是赋予这些数据意义的图表。如果我们拥有某个人的完美行为模式，那我们可以对此进行推断、衍生并试验。

有些行为确实有助于我们获取有利事物，而有些行为则具有浪费、消极、破坏的特点。借此，我们能够合理地选出某些有利行为，避免不利行为。我们用牙刷刷牙是为了保持牙齿洁白，但仅有极少数人会跳过这个步骤，直接采用漂白剂刷牙。

然而，我们并不擅长回避破坏性行为。一般而言，我们会选择那些不利行为，即使我们十分清楚它们可能产生的消极影响。比如抽烟、赌博与超速驾驶便属于不利行为。那么我该如何理解这些不合理行为呢？

关键是要理解，我们自身在决定那些在文化中既普遍又遭到限制行为这一过程中所发挥的作用。行为与想法似乎都拥有生命。

著名的进化生物学家Richard Dawkins在《自私的基因》一书中创造了“文化基因”一词，以此更好地解释文化的生成原理。作为游戏爱好者，你可能记得Huizinga曾经说过，游戏欲望能够激发文化形成，但这个理论模式并不完整。Dawkins以另一种方式解释了娱乐项目的盛行历程——即它们如何从孤立行为演变到文化领域。

文化基因是一组行为代码，也就是一种行为基因，它可以从某个个体复制到另一个个体上。文化基因能够构成行为。我们使用的语言、手势、短语，以及我们叠衣服、剪头发的方式都属于文化基因，而且它们是具有选择、遗传、变异三个特点。

在《自私的基因》一书中，Dawkins解释了自然选择如何作用于基因，而不是单个个体。进化方面的基因中心论有助于我们发现生物学的罕见现象。基因中心论表明，有些基因被复制的成功率大大高于其它基因。因此它们更能够体现自己的性能，久而久之，它们越发凸显，掩盖了那些不具优势的基因。

正是这个简单的发展过程衍生出了能够适应其周围生存环境的生物体。基因中心论能够解释疾病与癌症这些现象，现在，它的作用远远高于达尔文的进化理论模式。个体是一个由基因组成又能制造基因的机器，其唯一目的是复制基因。

虽然基因并没有明显存在物质世界中，但与此过程相似的想法诞生的自然选择过程，确实有助于我们理解糟糕想法扩散的原由。文化基因的生存状况并不取决于它对宿主的影响，而是取决于它向其它宿主完美传播的能力。文化基因似乎能够驾驭我们的大脑自动传送更多基因。行为与想法也具有病毒性质，如同基因一般，有时，我们很不幸地成为第二个基因复制的宿主。文化基因可以通过选择性传播（甚至是无意识选择），它们自我复制，变异为一系列全新、带有潜在病毒的想法。

在设计游戏时，我们不会完全受到这类基因的支配：我们能够引导文化基因向有利的方向进化。虽然我们无法选择某些特定基因，但我们能够改变它们的选择环境。通过精心设计基因的繁殖环境，预测可能发生的动态。

适应度函数能够评估某个物体的适用性。当针对遗传算法等编程时，我们能够完全控制适应度函数，我们可以自己编写它，但即使我们不是适应度函数的直接作者，我们仍能采用其他路径，模拟出它在我们创造的环境中的运行方式。

在真实世界中，我们已经目睹了长颈鹿进化为适应生存者的形象。它们的有利生存条件是能够长期存在并大量繁殖，而这需要稳定的食物来源，相对安全的生存环境，以及公平的配偶竞争机会。

它们的长脖子支持它们获取那些竞争不太激烈的食物，其数量会随着生存环境的改善不断增加。正如我们发现了那些尚未开发的高大茂盛的树木资源，就可以推测此地会出现长颈鹿这一物种，因此，我们可以通过检验游戏的某些制胜条件，预测可能催生出的事物。

Uroboric周期

每款游戏都附有针对性的制胜战略（行为），我们观察发现，在充足的时间内，行为会演变为有利取胜的战略。简而言之，随着时间的发展，玩家更容易在游戏中取胜。游戏设计师制定的规则将首次构成行为的适应度函数，因此，我们必须谨慎小心，确保内部规则制造的问题能够以我们期望的行为予以解决。我们制作的游戏应保证玩家采用我们期望中的最优制胜战略。当玩家要求的行为与最优制胜战略不匹配时，你的游戏就会沦落为一款毫无趣味、难以掌控与权衡的作品。

多人玩家的游戏环境会将这种情况演变得更加复杂。玩家的行为模式会改变游戏与适应度函数，并引发适应变化环境的新一代文化基因。

如何最优化地体验多人玩家游戏主要取决于其他玩家，而且，我们预期的普遍行为将是一组用于改变适应度函数的全新外部规则。uroboric平衡的这种迭代过程将会持续发展，直到出现某个可以成功控制整个基因组的文化基因。

游戏的内部规则主要充当适应玩家行为的首代适应度函数。随着不同战略的尝试，内部规则能够决定哪种战略更具成功性。

比如，在策略射击游戏中，缓慢关闭的十字线更有利于更为缓慢与系统性的玩家行动。在这种环境下，玩家的战略应是平衡精确度与移动性，随着时间的流逝，玩家将自然而然地以一种接近最优方式体验这款游戏。

然而，在多人环境中，玩家必须互相争夺有限资源。游戏中仅存在一些可以射杀的敌人，但玩家战略会向有利方向快速发展。当发生这种情况时，所有玩家将不得不面对新竞争环境——而它最初并非由游戏作者打造（游戏邦注：虽然游戏作者可能预料到了这种情况）。

玩家本身会成为环境的一部分，不断地影响并塑造游戏文化，推动其产生更棒的制胜战略。

《星际争霸2》与人工选择

随着游戏更具复杂性，要达到uroboric的最终平衡则需更长时间。有些游戏文化会持续多年的演变，而有些则在几分钟内便能取得平衡。

暴雪娱乐在竞技类游戏《星际争霸2》中植入了uroboric平衡周期的动态本质。为确保游戏的有趣与动态，每当某个文化基因占据主导位置，或是开发者想要刺激另一个基因发展时，他们便会稍稍调整内部规则。每当内部规则发生改变，它便会向uroboric周期注入大量动力，而后，游戏文化（游戏邦注：或者《星际争霸2》中的亚策略）也发生巨大变革。

此外，设计师有意在《星际争霸2》中设计出支持多种制胜亚策略的内部规则。因此，你会发现自己能够在每个情境中采取一些策略，而且它们均包含特定的平衡性。

然而，有些游戏则包含严格的直接规则，它们能够指示对某些情境采取的举措——你的游戏能力主要由采取特定行动的方式来衡量，但《星际争霸》并不重视你执行某个动作的能力，它主要关注你如何制定决策。当某个杰出玩家对游戏情境作出反应时，他/她所做的决策不仅要基于对敌人行动的了解，而且还应基于当前游戏对他们行动的预测。

《星际争霸2》属于一款复杂的即时战略游戏，游戏主要分为两个相互争夺资源与优势的作战派系。游戏需平衡经济与军事力量投资，允许你到达游戏的最终目标：完全摧毁对方基地。

虽然游戏本身相当复杂，但其内部规则却着实的简单与直接。隐藏摧毁敌人基地的取胜条件属于必经大事。为了破坏敌人基地，首先，你必须打败敌人的势力，这需要你打造自己的军队，以此增强基地实力，而相应支出则需要你收集一些额外资源。若无法采取以下举措，你的游戏则注定将以失败告终：

*收集额外资源

*建造支持军事单位训练的基础设施

*训练军事单位

*在战斗中打败敌人

*破坏敌人基地

虽然破坏敌人基地相当简单，但该过程为玩家的自由发挥与某些错误行为预留了空间。在筹资军队基础设施建造前，我应多频繁地提高经济条件？我应生产哪类军事单位？生产的数量是多少？我该如何部署军队以便打败敌人？这并不能在内部规则中找到答案，因为它们是游戏文化的一部分。

不久，那些另类的杰出玩家便快速掌握接近最优状态的建造顺序，这些全新建造顺序也将在游戏文化中遭遇激烈竞争。当游戏文化几乎都认同某个最佳建造顺序时，暴雪就会重新调整内部规则，让整个社区（可以是潜意识，或是通过努力）重新评估这一共识。

暴雪娱乐通过人工选择有益玩家与用户的娱乐价值，细致地引导《星际争霸》文化的发展。可以说，是内部文化推动了《星际争霸2》成为热门的有趣游戏。

但同样地，游戏文化也会对作品本身产生极大的不利影响。我在前面提到，开发者预期的行为可能无法与最优获胜战略相吻合，现在，我将举例论证这一观点。

《现代战争》与公地悲剧

《使命召唤4：现代战争》可谓是具有快节奏与高度紧张的热门第一人称射击游戏。要掌握这类玩法，玩家应具备快速的反应能力、完美的手眼协调技能，并采用平衡战略。掌握《使命召唤》的玩法并非易事，也并非每个玩家都可登上排行榜……至少，这也是游戏的目的。由于游戏的内部规则，《现代战争》中的Crossfire地图能够完美展示破坏性文化基因如何占据优势。

Crossfire地图由于支撑一系列不同玩法风格而大获好评，但其关键元素是为了引发某些挫败与普遍行为。对方团队会从地图的某一端为根据点，并设置多种建筑物与障碍作为分界线。为了能够触及敌人，你必须离开相对安全的区域，进入地图中间的危险战争地带。为了能够取胜，你必须艰难地平衡前进与后退战略——这是一场艰难挑战，但该地图为玩家的自由发挥预留了大量空间。由此可见，登上Crossfire地图排行榜之首确实是个艰难过程。

但玩家迅速发现了某些得分捷径。游戏一开始时，隔离两个团队的围墙十分低矮，因此他们可以随意互扔手榴弹。有些精确的统计概率能够指明敌人的大概位置，借此，你可能会获取“免费”分数。预定的起点模式与对方之间的不足障碍可能会导致某个创意玩家迅速死去。

首次发生这类事情确实令人印象深刻——为了发明这项技术，你应当充分了解游戏与地图。问题是，复制文化基因毫无难度，且不需要任何技术成分。

更多的玩家通过这道墙向对方投掷手榴弹，单个投掷手的得分机会也随之大幅减少，但同时提高了某个倒霉对手早点丧生的概率。这种“乱扔手榴弹”的文化基因无疑是不幸情况下的产物。

由于易操作性，该战略尤为玩家喜爱。他们在获取免费分数时，无需任何技能与努力，因此大量玩家转向这种玩法。而且这种玩法成本十分低廉——之后在Crossfire地图的快节奏环境下，使用手榴弹则变得尤为困难，因此你不妨在游戏初始时期投掷一些手榴弹，并寄希望于获取最佳效果。

获取最佳效果还应逾越第二道障碍。间隔性的随机奖励模式容易令玩家上瘾。其实，对投掷精确性的无知会令你如赌博般上瘾。而你所下的赌注是一颗廉价的手榴弹，作为回报，你可能会取得一些理想分数。我们很容易便能复制这种文化基因，因为我们通过观察便能理解哪些是必要行动，这是一种以低成本取得的成功，且会让人上瘾。

越多的人复制这类文化基因，其扩散速度也就越快，不久之后，该普遍基因会演变为预期行为。在游戏开始的前20秒，双方均会通过墙壁互投手榴弹，以此决定多少玩家会在游戏开始前阵亡。毫无疑问，在前20秒便退出游戏的玩家会感到十分郁闷——但如果你打算避免在早期丧生，你可以放弃这次机会。

当该文化基因变得十分普遍时，就没人可以从中获取优势。由于过多的玩家选择随机乱投举措，因此这种行为破坏了游戏的整体趣味。问题是，我们无法根除这种文化基因——相应地更改地图成本则十分高昂，而游戏也无法摆脱这些麻烦元素。这种病毒基因的传播速度极快，以致于我们难以遏制。游戏的内部规则更是提高了这类文化基因的传播速度；KillCams会在角色丧生前重播这一时刻，借此，我们可以快速发现受害者，并获得更多随机乱投机会。双方的队友可以选择并加入这种模式。

虽然在该基因被广泛采用之前，这是一种合理、有益且充满趣味的行为，但形势发生了转变。游戏中的仅限空间需供给大量玩家随机投掷手榴弹，但游戏却未设置阻碍玩家从事这一行为的机制。

从游戏理论的角度看，有关《现代战争》的这些事项可归结为公地悲剧，令人惊讶的是，这种情形几乎会发生在所有日常事务中。遏制这种传播速度、阻止公地悲剧方面的问题应依靠另一个典型理论“囚徒困境”来解释。

因为这类文化基因极易复制，玩家应协调配合，维持它的传播速度。如果有人同意摒弃乱投方案，那么游戏会更具趣味性。问题是，一旦有人停止了随机乱投举措，那么提出这一想法的玩家能提升获胜率——而只需某个反对者轻轻一推uroboric周期，它就回到公地悲剧情况。文化基因理论鼻祖Richard Dawkins在他1987年的纪实文章《Nice Guys Finish First》中完美地解释了公地悲剧与囚徒困境这两种现象。

值得注意的是，KillCam的设计是为了阻止玩家采用乱投手榴弹这种消极行为。虽然KillCam引进了一种惩罚糟糕行为的元素，但它也为文化基因的传播创造了新型的有效载体。类似KillCam这种战略是把双刃剑：一方面，它们可以惩罚行为错误的玩家，另一反面，它们又会引入更多采取错误行为的玩家。最终，《现代战争》制定的最佳制胜战略并不符合玩家的标准。

总结

设计师在创造游戏的内部规则时应谨慎小心，因为相对你的设计输入而言，游戏文化更易对游戏本身产生巨大影响。文化基因可能会发挥强大的积极效应，或者是产生消极影响，虽然它们无法被驯服，但我们却去可以设计引导它们繁殖方式的环境。（本文为游戏邦/gamerboom.com编译，拒绝任何不保留版权的转载，如需转载请联系：游戏邦）

When Players Make the Rules: On Memes and the Meta-Game

by Nils Pihl

Are players pushing your game in directions you never intended it to go? In this article, Gamasutra explores how games like StarCraft II and Call of Duty: Modern Warfare encourage good and bad player behaviors.

An interesting thing about games is that the player always helps design them. No matter how simple or complex the game is, there is always room for our own creative input. We add new rules, new contexts, new narratives and new measures of success, and we choose which of the original characteristics of the game we want to interact with. Games are much like books in this manner, and we will often find the most interesting things about games between the lines of the author’s instructions.

When designing games, this is both a blessing and curse. How the player behaves within the context of the game has an enormous impact on how enjoyable the game will be for the player, and game designers often find themselves struggling with how to encourage the players to play in a way that will be rewarding. Managing the expectations and behaviors of the player is a daunting task, but one of tremendous importance. Games that are well developed in every sense can still fall short to an unhealthy in-game culture. The game is only as good as the players.

So how does one manage, or even anticipate, how players might behave within the game? To understand how, we will first have to gain a rudimentary understanding of behavior itself.

Behavior is the way someone acts in response to a particular situation or stimulus. It’s important here that we don’t confuse behavior, which is a model for describing someone’s actions, with the actions themselves.

“I am going to sleep” is a good example of what an action might be, and “I will go to sleep after this TV show, even if I’m tired now” shows us what a behavior would be. Whereas an action could be described as a data point, behavior is a graph attempting to make sense of the data. If we have a good model for someone’s behavior, we can extrapolate, and derive, and experiment.

Some behaviors are particularly successful at achieving things that are good for us, while other behaviors can be wasteful, detrimental, and destructive to us. This helps us rationally choose some of our behaviors, and avoid others. We brush our teeth with toothpaste to keep our teeth white, but only very few will make the leap and attempt to brush their teeth with bleach.

But we aren’t that good at avoiding destructive behavior. We routinely engage in behaviors that are bad for us, even when we are very well aware of the negative effects the behavior might have. Consider things like smoking, gambling, unprotected sex, and speeding. How can we explain these irrational behaviors?

The key lies in understanding that the roles we ourselves play in determining what behaviors are prevalent in our culture are fairly limited. Behaviors and ideas seem to have a life of their own.

The famous evolutionary biologist Richard Dawkins coined the term “meme” in his book The Selfish Gene, in an attempt to better explain what generates culture. As a game enthusiast, you may remember that Huizinga thought that our desire to play was what generates culture, but that is not a complete model. Dawkins found a way to explain how the things that play generated got to be so popular — how they could move from isolated behaviors into the realm of culture.

A meme is a chunk of behavioral code — a behavioral gene — that can get copied from one individual to another. Memes are the building blocks of behavior. The words and gestures we use, the phrases we choose, the way we fold our laundry, the way we get our hair cut, these are all memes, and they are ideas that can be observed, copied, and mutated.

In The Selfish Gene, Dawkins explains to us how natural selection acts on the genes, rather than the individuals. This gene-centric view of evolution has helped shed a lot of light on some of the more peculiar aspects of biology. The theory shows us that certain genes are more successful at being reproduced than others. The more successful genes will outperform the less successful genes and, with time, we will see more of the successful genes than we will of the less successful genes.

This simple process generates organisms that are very well adapted to the environment they live in. The gene-centric view of evolution has helped explain things like diseases and cancer, and is now a more useful model than Charles Darwin’s own model of evolution. The individual is a machine built by and for genes, with the sole purpose of replicating genes.

Although they obviously do not exist in any physical sense of the word, imagining that same process of natural selection on ideas helps us understand why bad ideas spread. The survival fitness of a meme is not determined by the effect it has on its host, but rather by how well it propagates to other hosts. Memes seemingly hijack our brains and make us into machines for spreading more memes. Behaviors and ideas have a viral life of their own, just like our genes do, and we are the sometimes-unfortunate hosts of this second replicator. Memes spread through observation (even involuntary observation), and they copy themselves and mutate into new, potentially viral, strains of ideas.

When designing games, we are not completely at the mercy of these memes; there are ways for us to guide the evolutionary process of memes to a place we want. Although we can’t choose which particular memes will emerge from selection, we can alter the environment of selection itself. By carefully designing the environment that the memes will populate, we can make some predictions about what will emerge.

A fitness function is a model for evaluating the fitness of an entity. When programming things like genetic algorithms we are in complete control of the fitness function — we author it ourselves — but even when we are not the direct authors of the fitness function, we can approach it sideways and try to model how it would work in the environment we created.

In the real world, we can see things like giraffes evolving over time to fill a niche where they have an opportunity to thrive. The victory condition for a giraffe is to survive long enough to reproduce, and this will require a steady source of food, relative safety from predators and a fair chance at competing for a mate.

Their longer necks allow them access to a food source with less competition, and the population grows in response to the improved living conditions.Just like the possible emergence of something like giraffes can be predicted by seeing that there are untapped resources in the form of tall, lush trees, we can anticipate the emergence of certain behaviors by examining the victory conditions of the game.

The Uroboric Cycle

For every game, there are strategies (behaviors) for winning, and given enough time the behaviors we observe will drift towards strategies that are better at winning. Simply put, people will get better and better at winning the game with time. The rules that the designer of the game puts in place (the internal rules) are the first building blocks for the fitness function for behaviors, so we must take great care to make sure that the internal rules create a problem that is solved by behavior we want to observe. We need to create the game in a way that ensures that the optimal winning strategy is something that we want our players to do. When the desired behavior of a player is not aligned with the optimal winning strategy you can end up with a product that is unenjoyable for many, hard to manage, and difficult to scale.

In any game environment with multiple players, the situation gets complicated further. The way that players behave will change the game, and thereby the fitness function, and give rise to a new generation of memes in response to the changed environment.

How to best play a game with several players depends greatly on the other players, and the prevalent behaviors that we can expect from them act as a new set of external rules that will alter the fitness function even further. This iterative process of uroboric balancing will continue until one meme is successful enough to dominate the memepool.

The internal rules of the game act as an initial first-generation fitness function for player behaviors. As different strategies are tried, the internal rules will help determine which strategies are more successful.

An example of this could be how a slow-closing reticle in a tactical shooter will favor a slower, more methodical player movement meme. Player strategies in this environment will have to strike a balance between accuracy and mobility, and with time, players will intuitively play the game in an ever closer-to-optimal way.

In a multiplayer environment, however, the players will have to compete with each other for limited resources. There are only so many kills to go around, and strategies can quickly develop that are more competitive. When this happens, all players will have to respond to this new competitive environment — an environment that was not initially designed by the game’s creators (although it might well have been anticipated).

The players themselves become a part of the environment, constantly shaping the in-game culture towards better winning strategies.

StarCraft II and the Artificial Selection of Memes

The more complex the game is, the longer it will take for the uroboric balancing to reach a final equilibrium. For some games, the in-game culture keeps changing for several years, while other games reach an equilibrium in a matter of minutes.

Blizzard Entertainment takes advantage of the dynamic nature of the uroboric balancing cycle in its competitive game StarCraft II. To ensure that the game stays interesting and dynamic, Blizzard slightly alters the internal rules whenever a certain meme is getting too dominant, or if the developers want to encourage the growth of another. Whenever the internal rules are changed, Blizzard injects a great deal of momentum into the uroboric cycle, and the in-game culture (or the meta-game, in StarCraft II lingo) changes dramatically.

What’s more is that StarCraft II’s internal rules have been deliberately designed in a way that allows for a flourishing and diverse meta-game. Blizzard has made it so that for every situation that you find yourself in, there are several strategies for proceeding, each with its own special trade-off.

Some games have rather strict, straightforward rules that dictate how you should respond to a certain situation — and your prowess at the game is measured in how well you carry out that specific action — but in StarCraft II, the emphasis is not necessarily on how well you execute an action, but rather how well you make decisions. When a talented player responds to a situation in the game, he or she will make a decision based not only what he or she knows the opponent to be doing, but also on what the current in-game culture predicts is likely for the opponent to do.

StarCraft II is a complex real-time strategy game that pits two warring factions against each other in a struggle for resources and dominance. The art of the game is balancing your investments in economy with your investments in military might, allowing you to reach the game’s ultimate goal: the complete destruction of the opponent’s base.

Although the game is tremendously complex, the internal rules are surprisingly simple and linear. Buried in the internal victory condition of destroying the enemy base are several necessary milestones. To destroy the enemy base, you must first defeat the enemy’s forces, which will require you to have built forces of your own, which will in turn require you to have augmented your base with the infrastructure to allow for troops to be built, the cost of which will have required you to gather additional resources. Failing to do any of these is a guaranteed way to lose the game.

Collect additional resources

Build infrastructure to allow for the training of military units

Train military units

Defeat the enemy in combat

Destroy the enemy base

Although destroying the enemy base is pretty straightforward, the steps along the way leave a lot of room for personal style — and for mistakes. How much time do I have to improve my economy before I must invest in military infrastructure? What kind of military units should I produce, and how many, and how should I deploy them to defeat the enemy in combat? The answers to these questions are not coded into the internal rules, but are a part of the in-game culture.

Gifted and curious StarCraft players quickly start arriving at closer-to-optimal build orders over time, and these new build orders will then face tough competition in the in-game culture.

When the in-game culture reaches something close to a consensus on what the optimal build order is, Blizzard makes a change to the internal rules that will have the entire community (both subconsciously and through deliberate effort) reevaluate that consensus.

Blizzard Entertainment has carefully and meticulously guided the in-game culture of StarCraft through artificial selection to have as much entertainment value as possible for both players and spectators. What makes StarCraft II into such a popular and entertaining game is the in-game culture that it has spawned.

But in-game culture can have tremendously detrimental effects on a product as well. I mentioned earlier the possibility that the desired behavior and the optimal winning strategy might become unaligned, and I would now like to give you an example of this.

Modern Warfare and the Tragedy of the Commons

Call of Duty 4: Modern Warfare is a tremendously popular first person shooter — fast-paced and nerve-wracking. Being good at it required great reflexes, fantastic hand-eye-coordination, and a fair deal of strategic thinking. Being good at Call of Duty is hard, and not everyone can be competitive on the leaderboard…At least, that was the intent. The map Crossfire in Modern Warfare illustrates beautifully how a detrimental meme can gain a foothold because of the game’s internal rules.

The Crossfire map was very popular because it supported a range of different play styles, but there was a crucial design element of the map that gave rise to some of the most frustrating and prevalent behaviors in Modern Warfare. The opposing teams would start on either end of the map, separated by various buildings and other obstacles. To get to the enemy, you would have to leave the relative safety of your starting location and move into the more dangerous warzones in the middle of the map. To be a successful player on the Crossfire map, you had to strike a difficult balance between forward momentum and tactical retreats — it was a difficult map with a lot of room for improvisation. Topping the leaderboards on the Crossfire map could prove very difficult.

But players quickly found a way to get cheap points. One of the walls that separated the two teams early in the game was low enough for a grenade to be blindly thrown to the other side.

There was a good statistical likelihood that an enemy would be on the other side, and chance would determine if you got a “free” point or not. The combination of predetermined starting points and insufficient obstacles between the teams had allowed one creative player to get a stylish kill.

The very first time it happened it was undoubtedly impressive — to have invented the technique, you needed to have a very intimate knowledge of the game and the map. The problem was that the meme was easy to copy, without requiring any particular skill at all.

More and more people started blindly throwing grenades over that wall, which decreased the chances of each individual thrower getting a point — but increased the chances of a hapless opponent being unfairly killed early on. The “nade spamming” meme was the perfect storm of unfortunate circumstances.

The strategy was attractive to players because it was easy to use. Very little skill or exertion was needed to have a chance at a free point or two, so a lot of people gravitated towards it. The cost of trying it was also exceedingly low — in the fast-paced environment of the Crossfire map, it would be hard to use the grenades later on, so you might as well throw a few off early in the game and hope for the best.

And in hoping for the best lay the second rub. Random interval reward schedules can be incredibly addictive. The fact that you didn’t know if you would hit an enemy or not turned throwing the grenade into highly addictive gambling scenario. All you had to wager was a cheap grenade, and you could win very desirable points in exchange. It was a meme that was easy to copy because it was so easy to observe and understand the required actions, it was fairly successful at a low cost, and it was very addictive.

The more people copied the meme, the faster it spread, and after a while the meme was so prevalent that it was expected behavior. Both teams would throw grenades over the wall in the first 20 seconds of the game, and chance would determine how many players from either side would be taken out of combat before the battle even begun. Needless to say, being taken out in the first 20 seconds of the game is incredibly frustrating — but if you chose to avoid the situation where you could get killed early, you would forfeit an opportunity to stay competitive with your teammates.

Once the meme had become popular enough, no one really stood to gain anything from it anymore. Too many people were nade spamming, and the overall fun of the game was taking a severe hit.

The problem was that the meme proved very difficult to eradicate — the cost of changing the map itself was prohibitive, and for game hosts to kick offenders proved to be a task of Sisyphean dimensions. The viral meme was spreading too fast to be contained. The internal rules of the game made it fantastically easy for the meme to spread; KillCams would replay the moments before your avatar’s death, and the victims quickly caught on and reciprocated with more nade spamming. Teammates on either side observed the behavior and joined in.

Although the behavior had been perfectly rational, beneficial, and entertaining before the meme become widely adopted, the situation changed with scale. There was only room for so many people to nade spam, but there was no mechanism from preventing everyone from having a go at it.

In game theory, what happened to Modern Warfare is referred to as the Tragedy of the Commons, and it is a surprisingly common occurrence in all kinds of everyday situations. But the problem of containing the spread, and preventing the Tragedy of the Commons, is better explained with another game theory classic: the Prisoner’s Dilemma.

Because the meme was so easily copied, players would have to reach an agreement (explicit or otherwise) to cooperate in maintaining its spread. If everyone agrees not to nade spam, the game will be more enjoyable for everyone. The problem is that once people have stopped nade spamming, the winning potential for someone trying it gets very high — and it only takes one defector to nudge the uroboric cycle back towards the Tragedy of the Commons. Richard Dawkins, the father of meme theory, explains the phenomena of both the Tragedy of the Commons and the Prisoner’s Dilemma very well in his 1987 documentary Nice Guys Finish First.

Interesting to note is that the KillCam was designed as a way of deterring people from engaging in negative behaviors like nade spamming and spawn camping. Although the KillCam introduced an element of penalizing the bad behaviors, it also created a new and very effective vector for the memes to spread. Measures like the KillCam are double-edged swords: on one hand, they punish wrongdoers, but recruit more wrongdoers on the other. At the end of the day, Modern Warfare’s internal rules gave birth to an optimal winning strategy that was not in line with the desired behavior of players.

In Conclusion

Designers should take great care when creating the internal rules of their products, as the in-game culture that the game will inevitably have can have a greater impact on the product than your own direct design input. The meme can be a very powerful friend or foe, and although the meme cannot be tamed, we are ultimately the architects of the environments in which they spawn.(source:gamasutra)