作者：Travis Ross

我们的世界被一种相互作用包围。在这种相互作用对某些人有利，但对其周围的群体却未必如此。例如，污染、资源过耗、公路养护、帮助穷苦人的社会福利。这种情况通常称作N人社交困境（也称为社会两难问题）：有许多玩家（N个），每个人都有自私自利的念头，且自私的行为会对全体造成恶劣的影响。

在虚拟世界中，我们要幸运得多，因为资源是无限的。如果资源短缺，那就制定能源限制计划；如果怕污染问题，那就设计出一种不产生垃圾和其他副产品的产品就好了。但是，设计师通常不会将游戏设定为资源无限，因为人类行为的本性把物品的稀缺属性和动机及价值紧密地联系在一起。稀缺代表的是一种地位。稀缺产品代表的是技术和资源。物以稀为贵，稀缺物是独一无二和伟大的标志，所以收集并占有稀缺物的感觉往往不坏。在这种情况下，竞争和自私是胜利者的玩物。游戏是零和的，因为赢家夺得战利品，而输家只不过得到尝试的经验。然而，有时候稀缺的产品更值得储藏起来以备不时之需。此时，收获就是乐趣，是耐心和合作的资源。合作能把饼做大，每个人都能分得一小块。此外，确保合作还能产生一定的社会效益，如广播信任的种子、创造或巩固友情等。

除了资源稀缺，污染也会引发社交困境，污染可以由闹事或洗劫等不良的行为引发。在这些情况下，个人可能会受到与游戏发展无关的内在动机的刺激。也许他们享受统治其他个体的快感，或也许他们只是在尝试将合作变得更有竞争性。对滋事者动机的研究是有限的，但大多数人都曾撞上滋事，或者做过自私或反社会的事。

社交困境产生的另一个原因是，设计师可能有意无意地把社交困境纳入游戏里。过去，游戏特征是难以改变或移除的。这对喜欢竞争或自利游戏的玩家就有利，但对于想结交朋友或想换换口味、参与合作社交的玩家来说，至少得有一个机制允许团队避免社交困境的自私后果产生。在一些机制不太管用的游戏中，自发团队利用第三方资源或其他方法作为团队成形的基础，以解决社交困境的难题。

在下面的部分，我将具体谈谈几点社交困境的研究成果。我将重点探讨如何提升或增加合作的发现成果。这些并不值得做成文献综述，所以我只是指出基本理论的来源。此外，我会列举相应的游戏场景案例作为成果运用示范。但愿勤奋的游戏设计师可以利用这些发现来识别或生成解决社交困境的设定；也许更重要的是，运用这些发现来设计能鼓励合作、又有助于形成稳固的线上友情的游戏机制。

一、二和三：反复、声望和伙伴选择

社交困境研究

1980年间，在一件与游戏理论相关的创意事件和策略选择研究中，密歇根大学的政治学教授予Robert Axelrod主持了一场比赛，要求参赛者针对“囚徒困境”设想出各种不同的策略。这场比赛的亮点在于， Axelrod邀请了世界著名的社会学家参赛。每个人所想出的策略都是他们自认为的最佳方案。比赛的结果特别有意思，最终脱颖而出的居然是一个非常简单而又比较合作的策略。它就是“一报还一报”（游戏邦注：Tit-for-tat，或者说是以牙还牙）。

为了揭开“一报还一报”策略胜出的真相，首先要理解这场比赛的发生情境。更详细地说，囚徒困境显示了，合作导致了玩家的欺骗和背叛。事实上，囚徒困境的纳什均衡是互相背叛，但在Axelrod的比赛中，有两个关键特征，能使合作比背叛更胜一筹。（游戏邦注：Nash Equilibrium，纳什平衡，又称为非合作平局，是博弈论的一个重要概念，以约翰·纳什命名。也就是，如果某情况下无一参与者可以独自行动而增加收益，则此策略组合被称为纳什均衡点。）

第一个特征是反复性。因为Axelrod的比赛的作用前提是多回合，多回合保证了合作可以比背叛产生更好的结果。如果两个玩家可以选择长期合作，结果会比两人相互背叛要好。然而，背叛者和合作者只搭档一个回合，或保持匿名，仍然可以产生较好的结果。

为了保证互相合作的成功，还必须搭配其他条件。玩家首先必须有能力识别过去与之合作过的人。处于一个你期望形成合作到头来却被他人出卖的群体中，识别的条件就没有意义了。此时，玩家必须保有记忆和声望。这个特征允许合作者只和其他合作者合作，因为他们可以识别背叛者、并以互相背叛制裁他们。

在游戏设计中的应用

不止是社交困境，声望、反复和伙伴的选择对任何游戏设计都很重要。几乎所有现代在线多人游戏都具有反复匹配系统，然而，反复匹配系统的出现形式是多种多样的。值得注意的是，反复匹配系统的一个重要参数是声望。有了声望标记和恰当的反复匹配系统，玩家可以避开那些过去惹过事的玩家。另外，有些公司已经制作了识别骗子和问题玩家的机制。这种机制可以移除这两类玩家，这样玩家就可以安心地参与到反复匹配系统中，而不必害怕与骗子、抢夺犯、滋事者和傻瓜为伴了。

反复随机匹配： 玩家被随机与其他玩家相组合。根据团体的规模，你可能不会两次见到同一个人。随机匹配在早期的在线游戏中运用得比较广泛。然而，当游戏开始登陆GameSpy、Steam、Facebook和Xbox Live等各平台时，随机匹配就已经让位于更复杂的导向型匹配系统。然而，我们还是能够在FPS类、运动类和RTS类游戏等中见到随机匹配的身影。

反复导向匹配： 玩家在一定的特征范围内与其他玩家进行配对，这个特征范围包括声望、经验和操作风格。被数据和参数跟踪的玩家档案需要一定程度的持久性。导向匹配有别于自行选择，因为它需要第三方的引导（通常是计算机算法）。

反复自行选择： 允许玩家自己选择他们的同伴。反复自行选择可以作用于一定的情形，如在MMO公会中，玩家可以花点时间慎重地选择；但是，如果这款游戏需要频繁配对且阻碍内在动机性玩法，这可能会拖慢游戏的进度。试想一下在欺骗性比赛中尝试验自行选择。大多数游戏在此显示出适当和明显的特征——提供自行选择和导向匹配两种选顶。以《魔兽世界》为例，这款游戏只允许自行选择（如地下城），该特征被许多MMO游戏追随。过去暴雪意识到玩家正在创造自己的紧急配对系统（在五人地下城突袭中，玩家较少挑剔），暴雪就能够为玩家提供导向系统（地下城发现者），该系统组织建立联机团队、为玩家节省了相当多的时间、鼓励临时团队。

空间

到现在为止，我一直在谈所有人所生存的探索空间的匹配系统。唯一对空间产生约束的就是信息过滤。然而，像MMO这类游戏存在实体空间。尽管匹配系统好比移除这些限制的地下城发现者或拍卖行，空间仍然值得作为匹配玩家的机制。例如，MMO游戏提供了一种匹配玩家的方式，即组合同一个任务的玩家或正在寻找交易同伴的玩家。显然，如果认同空间作为一种匹配机制，但空间的特征是往往缺乏变化系统，如Xbox-live和一些我们认为理所当然的东西。空间在社交困境的研究中也占据相当重要的部分，这是因为空间立体基阵影响不同策略的成功和失败。

空间还能帮助玩家发现其他与之有相同需要和利益的人。例如，《Rift》利用空间事件将玩家过虑到公共团体中。在这里，匹配系统是纯粹的自行选择。对该事件有兴趣的玩家们只需要寻找另一些已经加入的玩家（《Rift》的设计师应该考虑到这是挑战所在），然后他们可以组成一个有着共同目标的公共团队。在此，空间根据目标、利益和动机划分群体。

声望

声望系统与匹配系统存在密切的联系。声望可以帮助玩家迅速对另一个特定玩家的信任值做出判断。关于声望的科学文献并不少，足以汇成一份报告或者一册书。在线游戏和社交媒体中的声望系统已经变得越来越重要，因为该系统解决了玩家之间的协调问题。声望系统通常与反欺诈系统相组合，以过滤玩家可识别出来的问题。另外，声望系统还为团体成员提供了避免问题玩家的第二层级声望。目前存在非常多类型的声望系统，我所讨论的是我认为具有某些重要成分值得一提的系统。在大多数关于社交困境的科学文献的描述里，匿名滋生背叛。当其他人不能识别他们，玩家就非常可能做出背叛的举动，因为匿名的玩家不可能受到处罚。一般而言，声望系统的核心在于，创造一种很难采有匿名形式的系统，这看似简单，但对在线环境仍然是一个挑战。

持久性：首先是建立持久性玩家个人档案。当玩家档案存在于游戏和玩家之间，玩家必定会更加关注自己的声望。在社交网络档案永久化以前，玩家的中间层级档案存在是准则。

转换成本：如果没有一定的转换成本，那么所谓持久性也不会实现真正的价值。如果玩家不需要为转换付出代价，那也就无所谓抛弃旧档案，再建立新档案。也就是说，“当前档案有污点，大不了再做一个。”所幸的是，许多东西能提高转换成本。绑定的虚拟物品存在真正的价值，并且已锁定个人。在Facebook档案上建立一个新ID要付出一定费用（当你使用真实ID时成本更高）。像地位和成就这类简单的东西也可以增加转换成本。

摩擦：当然，傻乎乎的玩家可以简单地制作一个假帐户就为所欲为。这就是将帐户与真实ID和信用卡捆绑的价值所在。摩擦通常被认为是网页开发者的祸害，但考虑到声望，摩擦也是转换成本的必要部分。如果建立一个新帐户需要花费一定时间、需要信用卡、付费、手机号码绑定或者与要经过激活期，那么，被声望提高的转换成本就会有更多持久性。

四、互惠

一些科学家认为互惠是人类天性的本能，这是因为进化的压力偏爱那些投身于互惠交易的人。在之前的博客里我详述了这种可能性。因为我曾经在互惠的话题上涉猎了一些文献，所以我很快就注意到互惠可以促进社交困境中的合作，因为它允许从交易中获利、便利了交流和创造持续的个人和和团体之间的关系。

一些学者提出质疑，社交游戏是否利用人类对互惠固有的渴望来从恶。然而，互惠也是一股善的力量。我在此罗列了一些利用互惠的游戏机制（我只是列举其中一部分，而不是全部）：

《Left 4 Dead》允许玩家治疗另一名受伤的玩家。不纯粹为了保持他们的健康，而是希望今日的同船共济，能够换来明天的同甘共苦。

大多数MMO游戏带有需求/贪婪/传递的特征。认为自己乐意传递或贪图一些没有当即用处的物品，以备来日的互惠之用。

《Settlers of Catan》允许玩家互相交易。互惠同盟的形成环境通常是，在玩家带着增加胜算的希望，互相进行有利可图的交换。

社交游戏玩家一般能够赠送礼物，当然，大家都希望得到回馈。

团队运动，如篮球运动，为了让整个团队有更出色的表现，需要一起传递一个球。成员的希望是，如果我把球传给你，让你扣篮，之后你也得给我相同的表现机会。

这些只是一点粗浅的分析，如果你想到其他情形，不妨自由评论。

如何围绕互惠建立一种游戏机制：

1．给予玩家互惠的途径。如果玩家没有机会进行互惠交换，那么玩家就不会这么做。通常是稀缺、交易所得和专门化为玩家的互惠活动提供一种机制。如果你的游戏平台存在大量差异性，就有必要对空间进行重要考虑，即利用空间导向具有相同利益的玩家，或者将玩家纳入利益共同体中。

2．确保玩家可以交流自己的意图。在互惠交易中，第一个行为无私的玩家就将自身暴露于被背叛的危险境地。如果玩家可以迅速有效地交流意图，就可以减少玩家之间的疑惑和意外背叛的发生。为玩家提供制造信用威胁的机制可以增进合作。当玩家可以进行报复时，背叛行为也可能会减少。如前文所述，通过持久性声望可以达到这个目标。

3．给予玩家再次交互的理由。一旦玩家已经互相帮助，不要让这种积极的感受和合作消失。给予双方再一次合作的机会。

五、回报结构

显然，社交困境的回报结构可以增加或减少合作，但社交困境研究中更有意思的发现之一是，采取某种策略或制造结构性改变可以使“囚徒困境”（其平衡点在于相互背叛）变成一种“确信博弈”（平衡点在于相互合作）。

将“囚徒困境”转化为超乎第一种相互作用的“确信博弈”的“一报还一报”是一种长期性策略的例子。“一报还一报”将所谓的信用承诺分为两种策略，即允许对手在任何过去的相互作用中首先意识到自己拥有两种选择：互相合作或互相背叛。

开发者可以利用游戏理论来映射某种设计元素的基本回报结构。发生在游戏中的背叛问题看似因为开发者不能充分考虑到背叛对玩家的诱惑而造成的。盘算玩家的动机是一个困难的命题。玩家通常不是透明的，且他们可能是在探索游戏的极限，或做其他意料之外的事的过程中发现内在动机。在这些情况下，仍然有必要理清游戏的基本结构。玩家行为的意外性可以通过游戏理论提供的基本原理得到粗略的形式梗概。通过重组游戏的回报结构或允许玩家调整自己的策略，开发者可以尝试着避免玩家的背叛行为，同时增进合作。

六、交流

研究表明，引入交流渠道或增加带宽几乎总是能在社交困境中引发更多合作。然而，正如我们在许多游戏中所看到的，交流与匿名相结合，可以导致更多的滥用和噪音污染渠道。在我之前所写的文章中，我已经探讨了什么交流渠道会受到公害的影响。

七、奖励

关于社交困境的研究往往将关注焦点放在，将处罚用于防止自由放纵和背叛的使用方法。然而，近年来，大概是因为游戏的影响，社会科学家已经开始将目光投向奖励。游戏设计师在奖励“理论“方面，当然比社交困境研究学者们走得更远得多。证据表明，谨慎使用奖励可以促进合作，同时得到比处罚更高的整体回报。当游戏开发者设计系统时，他们应该考虑：通过奖励或处罚玩家，是否会有更高的总体满足感。处罚的力量往往比奖励更强大，所在一些情况下，禁止某些行为比确保每个人都得到奖励更为重要。再者，简单的游戏理论性动机模式对设计师判断奖励或处罚是否合适大有帮助。

为了增进合作，奖励系统可以纳入游戏中，以激励以下几点：

为公/或不污染：在不污染或为公的情况下，证据表明，奖励系统会激励贡献和减少背叛。因此，合作也会相应增加。

指导/帮助/亲社会：奖励指导他人的玩家是增进合作的好方法。事实上，如果能够鼓励地位高的玩家帮助别人，也许可以广泛传播亲社会行为或指导的规范。

处罚的形式可以多样化。最普遍的是：

玩家驱逐：玩家有权处罚另一名玩家。与交流渠道类似，如果这种处罚不能在制约与平衡的前提下进行，就会打开一道滥用的大门。玩家驱逐处罚确实让玩家获得了监管自身的机会。在社交困境研究中，自我管理往往产生一种管理系统或资源的权力和建立尊重和合作的规范。玩家驱逐系统并不会受到一些监督问题的干扰，而其他系统则会受到监督问题的破坏，这是因为相比于自动系统，人类在反社会的特征下更合谐。再者，持久声望是这类系统的重要因素。

自动：自动系统能够发现特定属性的玩家并驱逐他们。随着机器学习算法越来越复杂化，人工代理的出错率大大减少，最终代替人力监督游戏世界将指日可待。直到那时，误报和发现反社会行为的无能将不再困扰这些系统。

GM仲裁：对游戏开发商来说，这种方法虽合理但成本高。GM（Game-master，游戏管理员）受雇调查问题，与玩家群体不同，GM一般不会滥用他们的仲裁权力，也能够发现问题，而自动系统则没有这样的优势。

最后，游戏公司还可以混合使用所有以上策略。实际上，游戏结合使用奖励和处罚已经不是一朝一夕的事了。我非常欣赏的一种将奖励和处罚组合利用的方法已经写在《Speed Camera Lottery》这篇文章里了。

八、效力

在最后的机制，我想扭转一下局面。如前所述，我已经讨论了社交困境对游戏的启示。然而，读者看到这点时，可能会想，游戏也可能教政策制定者和制度设计者一些重要的东西。我完全赞同。关于奖励的部分，我提到，在奖励的问题上，游戏设计师可能比社交困境研究学者了解的多得多。我相信游戏设计师和游戏机制也在增加效力和意义方面也能带来不少启发。

公共利益的生产函数的表现为阶梯函数，或者说增长坡度相当缓。这种情形包括循环、对话、搞慈善或纳税等。个人相关的数值和反馈缺失使个人很难发现与归功于个人贡献的显著增长。社交困境研究已经表明，效力的单一看法导致对公共利益贡献的增长。组织机构知道且理解这个问题。试想一个由捐献人和支助人家庭组成的组织，他们证明捐献人每天的几分钱贡献确实有影响。这些系统也常常与其他反馈合作，如与受资助家庭通信和照片。

当生产函数表现为阶梯函数，产出的增长将非常显著，直到达到阀限。如果个人确信为了达到阀限，只需要一些捐献就足够了，（研究已经显示）贡献可能会增加。另外，研究还表明，如果各个玩家都明白个人贡献对利益供给相当重要，将玩家置身这样的群体中，整体利贡献将增长。这里的关键还是找出一种方法使个人确信自身贡献关乎整体的成败。

新游戏化运动的任务之一是，想出如何使玩家超越只为个人奖章和成就而感受到一种真正的意义。试比较一下，得到成就的心理回报和使最后贡献发展到生产函数的下一阶的心理回报。社交媒体和游戏结构为我们提供了一种将表达式破裂为几个小步骤函数的机制。如果我可以加入一个收纳数百名好友的Facebook团体，这个团体成员每月都循环利用他们的塑料、玻璃和纸，那会怎么样呢？想像一下，如果Facebook可以显示出捐赠量如何改善空气质量、节约垃圾填埋空间和制造新材料。James Cummings在他的一个贴子中向我们展示了斯坦福大学如何制作一个促进有效利用能源的游戏。我希望这只是冰山一角，游戏开发者可以启发决策者该如何增加对社会有意义、有效力的合作和减少投机取巧行为。（本文为游戏邦/gamerboom.com编译，如需转载请联系：游戏邦）

Eight Mechanics to Enhance Cooperation in Online Games

by Travis Ross

Travis Ross is a Ph.D. Candidate in Communication & Cognitive Science at Indiana University. This and other work from this author can be found at: www.motivateplay.com

As we move through the world we sometimes find ourselves in interactions where what is best for ourselves is not best for those around us. Pollution, overuse of resources, the maintenance of roads, and welfare for the poor and unfortunate are all examples. This type of situation is often referred to as an n-player social dilemma: there are a number of players(n), there is a temptation for individuals to act selfishly, and selfish behavior has negative consequences for the group as a whole.

In virtual worlds it may seem that we are fortunate because resources can be unlimited. If energy shortage is a problem, just program in unlimited energy. If pollution is a problem, just design production so there is no waste or byproduct. However, having unlimited resources in games is often not an option for designers because the nature of human behavior ties scarcity to motivation and value. A quick glance at a supply and demand curve can demonstrate that scarcity drives up price. Scarcity is also closely tied to status. A scarce good is a signal for skill or resources. It feels good to collect and own things that are scarce because they are generally valuable, or they signal that you are unique and awesome. In these scenarios competition and selfishness are fun for the winner.  The game is zero-sum in that the winner gets the spoils and the losers get only the experience of trying.  However, sometimes when a good is scarce, it can be more rewarding to preserve or sustain the resource for all to use. In these situations there maybe gains in fun, or even resources for patience and cooperation. Cooperation makes the pie bigger and everybody gets a slice. In addition, there are social benefits as the ensuing cooperation sows trust and creates/consolidates friendships.

Besides situations with scarce resources,  social dilemmas can also occur as a result of pollution, which can occur via undesirable behaviors like griefing or ninja looting – see my post on communication channels in Brink. In these situations, an individual maybe motivated by an intrinsic motivation that is not directly related to advancement in the game. Perhaps they enjoy dominating another individual, or maybe they are just trying to make a cooperative experience competitive. Research on the motivations of griefers is limited, but most of us have probably been on the butt end of griefing, or experienced someone playing in a selfish or anti-social fashion.

Another reason social dilemmas might exist is that designers may accidentally/or intentionally design them into the payouts of a game. Once a feature is in the game it can be hard to change or remove. This may lead to fun and excitement for players who enjoy competition or selfish play, but for social players who want to make friends, or those who want to try and cooperate for a change of pace, it is preferable to at least have a mechanic available that allows a group to avoid having only selfish outcomes in social dilemmas. In some games where social dilemmas were not solvable via game mechanics emergent groups have formed using third party resources or other means to provide a solution.

In the following section I will detail some of the findings from research on social dilemmas. In doing so, I will focus on findings that detail how to promote or increase cooperation. It’s worth noting that I won’t be doing a literature review. Rather, just pointing out where the basic idea comes from (if you have questions about further reading feel free to get in touch). In addition, I’ll provide some examples of game scenarios where this type of research could be applied as a game mechanic. Hopefully, enterprising game designers can use these insights to recognize and, when necessary, build in features that allow social dilemmas to be solved, and perhaps more importantly use these findings to design game mechanics that incentivize cooperation, and allow them to more easily form stable friendships in online games.

1,2, & 3: Iteration, Reputation, and Choice of Partners

Social Dilemma Research

During 1980, in one of the seminal events involving game theory and strategy selection research, Robert Axelrod, a professor of political science at the University of Michigan, held a tournament that pitted various strategies against one another in a repeated prisoner’s dilemma. What made the tournament unique what that Axelrod invited famous social scientists from all over the world to submit strategies that they believed would excel and then pitted them against one another. The results of the tournament were particularly interesting because a very simple and relatively cooperative strategy won. Its name was Tit-for-tat.

In order to understand why Tit-for-tat was able to succeed, it is first important to understand the context in which the tournament was played. Looking at the prisoner’s dilemma in more detail shows that being cooperative opens a player up to deception and defection. In fact, the Nash equilibrium of the prisoner’s dilemma is mutual defection, but there were two key features that allowed cooperation to be more successful than defection in Axelrod’s tournament.

The first feature is iteration. Since Axelrod’s tournament was played over multiple rounds sustained cooperation could do better than defection. If two players could team up they could do better by cooperating over the long run than two players who were defecting. However, defectors who pair up with cooperators for just one round or remain anonymous can still perform well.

In order for mutual cooperation to be successful other conditions must exist as well. Players must first be able to identify those who have cooperated with them in the past. In a population of players it isn’t useful to cooperate expecting mutual cooperation and have the other player defect against you. In this situation, players must have both memory and reputation must persist. These features allow cooperators to cooperate solely with other cooperators since they can identify defectors and sanction them with mutual defection.

Implications for Game Design

Reputation, iteration, and choice of partners are important features for any game design not just social dilemmas. Almost all modern online multiplayer games are iterated and feature matching systems, however, iterated matching systems can come in a variety of forms. It is worth noting that an important variable in iterated matching systems is reputation. With reputational markers, and an appropriate iterated matching system, players can avoid players who have caused problems in the past. In addition, some companies have created mechanisms for identifying cheaters and problem players. Allowing them to remove these players from the system, which lets players engage in iterated random matching with less fear of being matched with cheaters, ninja loots, griefers, and jerks.

Iterated Random Matching – Players are matched randomly with other players. Depending on the size of the community you might never see the same person twice. Random matching was used more often in the early days of online gaming. As games have begun to sit on meta-platforms like GameSpy, Steam, Facebook, and Xbox Live random matching has given way to more sophisticated guided matching systems. However, random pairing can still be found in a wide range of games such as FPS, sports, and RTS.

Iterated Guided Matching – Players are matched with other players on a range of features including reputation, experience, and play style. Some degree of persistence is entailed in the player profile as stats and preferences are tracked. Guided matching is different from self-selection because it is guided by a third-party (generally a computer algorithm).

Iterated Self-Selection – Players are allowed to self-select their partners. Self-Selection works in some conditions like MMO guilds where players can take time to be choosey, however it may actually slow the process of play in games where pairing must occur frequently and holds up more intrinsically motivating elements of play. Imagine trying to self-select each group in CoD match. Most games provide the appropriate and obvious design feature here; providing options for both self-selection and guided matching.  Consider World of Warcraft, which followed in the footsteps of many MMOs by only allowing self-selection for instanced dungeons. Once Blizzard recognized that players were creating their own emergent matching systems (players are less picky about 5 man dungeons that raids) Blizzard was able to provide players with a guided matching  system (Dungeon Finder) that build groups on the fly, saved players considerable time, and incentivized pick-up groups.

Space

So far I have been talking about matching systems where everyone exists in a search space. The only constraint to space is filtering information. However, games like MMOs have physical space. Although matching systems like a dungeon finder or an auction house remove these constraints, space is still worth considering as a mechanism for matching players. For example, in MMOs space provides a means for matching players who are on the same quest or are looking for a trade partner. It seems obvious when I identify space as a mechanism for matching, but space is a feature that meta-systems like Xbox-live often lack and something that we take for granted. Space also plays a big role in social dilemma research1. As spatial configurations influence the success and failure of different strategies.

Space is still an useful way to allow your players to discover others with similar needs and interests. One example is how Rift uses zone events to filter players into public groups. Here the matching system is purely self-selection. Players who are interested in participating in the event simply need to find other players who are participating – Rift designers should consider that this is sometimes a challenge – and then they can join a public group where they know everyone is trying to achieve the same goal. Here space segregates the population based on goals, interests, and motivations.

Reputation

Reputation systems are closely tied to matching systems. Reputation provides players with a mechanism for quickly determining if a given partner is trustworthy. There is a very wide range of scientific literature on reputation – enough to fill its own post, or even a book. In online games and social media reputation systems have grown in importance because they solve coordination problems for players. Reputation systems are often combined with anti-cheat systems to filter out the problem players who are recognizable. They also provide a second level of reputation for members of the community to avoid problem players. There are a wide variety of reputation systems that exist, and I am going to discuss what I believe are a few important elements of them. In most of the scientific literature on social dilemmas anonymity breeds defection. Players are probabilistically more likely to defect when others can’t identify them because when a player is anonymous it is impossible to sanction them. In general the key to reputation systems is to create a system that makes it difficult to be anonymous, which seems easy enough but can be a challenge in online environments.

Persistence – The first place to start is by creating player profiles that are persistent. When a players profile exists at a meta-level and travels between games the player must be more concerned about their reputation. Before social networks most profiles were not persistent, but now it is the norm for a meta-level profile to exist for a gamer.

Switching Costs – Persistence isn’t really that useful without some switching cost. Without switching costs a player has no repercussions for leaving their old profile and staring a new one. The thought here is, “If my current profile gets a bad reputation then I can just make another one”. Luckily there are many things that raise switching costs. Bound virtual items have real value and are locked on the character. Facebook profiles have the cost of creating a new identity (high cost when you use your real identity to begin with). Simple things like stats and achievement can add to switching costs.

Friction – Of course a player who wants to be a jerk could simply create a fake account and go to town. This is where tying accounts to real-ids and credit cards has value. Friction is generally thought of as the bane of web-developers, but in the case of reputation friction is an essential part of the switching cost. If creating a new account takes time, requires a credit card, costs money, is tied to my phone number, or has some sort of activation period, then switching costs are raised an reputation is by consequence more persistent.

4: Reciprocity

Some scientist argue that reciprocity is intrinsic to human nature because evolutionary pressures favored those who engaged in reciprocal transactions. In a previous blog post I detailed how this might be possible. Given that I’ve covered some of the literature on reciprocity in the past I’ll quickly note that reciprocity can improve cooperation in a social dilemma because it allows for gains from trade, facilitates communication, and creates ongoing relationships between individuals or groups.

Some writers including members of this site have questioned if social games are using the innate human desire for reciprocity for evil. However, reciprocity is also a force for good. I’ll list some mechanisms that take advantage of reciprocity in games (I won’t cover nearly all of them):

Left 4 Dead allows players to heal one another when they are injured. Rather than keep the health for themselves they can share in the hope that someone will share with them in the future.

Most MMOs Have a Need/Greed/Pass feature. Individuals who establish that they are willing to pass or greed on items that are not immediately useful to them expect future reciprocal exchange.

In Settlers of Catan allows players to trade with one another. Reciprocal alliances often form where players make mutually beneficial exchanges in hopes of increasing the probability of winning.

In Social Games players often have the ability to give gifts to others. The hope is that other will return the favor.

Team Sports require a sharing of a ball or puck in order to make the team better. The hope is that if I pass the puck or ball to you for a tap in, you’ll do the same for me later.

These are only scratching the surface so feel free to comment if you can think of additional situations.

How to build a game mechanic around reciprocity:

1. Give the players a means to reciprocate If there are not opportunities for reciprocal exchange then players won’t be able to do so. Often scarcity and gains from trade and specialization provide mechanism for players to reciprocate with one another.  Space is an important consideration if your game has a lot of diversity. Using space to direct players who have common interests, or putting players with common interests into groups is a means to achieve this.

2. Make sure players can communicate their intentions. In a reciprocal transaction the first player to act altruistically puts themselves in danger of defection. If players can communicate their intentions quickly and efficiently it can lead to less confusion and reduce the chance of accidental defection. Providing players with a mechanism to make credible threats can increase cooperation. When a player can retaliate defection becomes less likely. One easy way to do this is through persistent reputation, for the reasons listed above.

3. Give the players a reason to interact again. Once players have helped each other don’t let the positive feelings and cooperation fade away. Give those two players another opportunity to cooperate.

5: Payoff Structure

It may seem obvious that the payout structure of a social dilemma can increase or decrease cooperation, but one of the more interesting findings of social dilemma research is that playing certain strategies or making structural changes can make a prisoner’s dilemma (where the equilibrium is mutual defection) into an assurance game (where the equilibrium is mutual cooperation).

Tit-for-tat is one example of a long term strategy that turns a prisoner’s dilemma into an assurance game beyond first interaction. Tit-for-tat makes what is often called a credible commitment to only two strategies. Allowing opponents to recognize that in any interactions past the first they have two options. Mutual cooperation, or mutual defection.

Game theory can be used by developers to map the basic payout structure of certain design elements. It often seems that problems with defection occur in games because developers did not adequately consider the temptation for players to defect.  Figuring out player motivation is a difficult proposition. Players are often not transparent and may find intrinsic motivations in exploring the boundaries of a game or doing unexpected things. In these cases it is still worthwhile to understand the basic structure of the game. Game theory can provide the elements to sketch a rough formalization of why players are behaving in unanticipated ways.  By rearranging the payout structure of the game or letting other players adjust their strategies developers can try and avoid defection and increase cooperation.

6: Communication

Research demonstrates that introducing communication channels or increasing bandwidth almost always leads to more cooperation in a social dilemma. However, as we have seen in many games, communication coupled with anonymity can lead to another channel for abuse and noise pollution. In my previous post I explored why communication channels suffer from pollution.

For those who are interested in designing communication systems that are less prone to abuse read on here.

7: Rewards

Research on social dilemmas has typically focused on the use of sanctions as a means to prevent free-riding and defection. However, in recent years, probably due in part to the influence of games, social scientists have begun to focus on rewards. Game designers are certainly far ahead of social dilemma researchers when it comes to a ‘theory’ of rewards. Evidence suggests that the careful use of rewards can lead to more cooperation and an overall higher payout than sanctions. When game developers design systems they should consider if players will have a higher aggregate satisfaction through rewards or sanctions. Sanctions tend to be more powerful than rewards, so in some cases preventing the behavior is more important than making sure everyone can earn rewards. Once again a simple game theoretic incentive model can go a long way toward helping designers understand if rewards or sanctions are appropriate.

In order to increase cooperation a reward system could be built into the game to incentivize the following things:

Contribution to the public good/or not polluting – In the case of not polluting or contributing to a public good, evidence suggests reward systems will incentivize contributions and decrease defection. Hence, cooperation is increased.

Mentoring/Helping others/playing in a pro-social fashion – rewarding players for mentoring others is a good way to increase cooperation. In fact, if players with high status are encouraged to be mentors they may spread norms of pro-social behavior or mentoring.

Sanctions can take a variety of forms. The most common are:

Player-driven – Players have the power to sanction one another. Like communication channels, this opens a powerful avenue for abuse if the player-driven sanctions do not operate under checks and balances. Player-driven sanctions do offer an opportunity for players to take ownership of policing themselves. In social dilemma research self-policing often provides a sense of ownership over the system or resource and creates norms of respect and cooperation. Player-driven systems also don’t suffer from some of the surveillance problems that other systems suffer form, as humans are more tuned to anti-social patterns than automated systems. Once again, persistent reputation is an important factor for these kind of systems.

Automated – Automated systems find players who exhibit certain properties and expel them. With increasingly sophisticated machine learning algorithms it may not be long before artificial agents are able to police game worlds with very low error rates. Until then these systems suffer from false positives and an inability to detect many forms of anti-social behavior.

GM Based arbitration – For game developers this can be a reasonable, but costly solution. Game-masters are hired to investigate problem behaviors. Unlike player communities game-masters don’t generally abuse their powers of arbitration, and they can also detect problems that automated systems can’t.

Finally, there is nothing that says companies can’t use a mix of all these strategies. In fact using rewards and sanctions together is something that games have done for a long time. One interesting application of rewards and sanctions working together that I really like can be found here it’s called Speed Camera Lottery.

8: Efficacy

For my final mechanic I want to turn the tables. In the previous sections I have been discussing what social dilemmas can teach games. However, the reader up to this point might be thinking that games can probably teach policy makers and institutional designers important things as well. I completely agree. In the section about rewards, I mentioned that game designers probably know much more about rewards than social dilemma researchers. I believe game designers and game mechanics also have a lot to offer when it comes to increasing efficacy and meaning.

Often the production function of a public good takes the form of a step function or has a very slowly increasing slope. Situations like this might include recycling, conservation, making charitable contributions, or paying taxes. In these situation the number of individuals involved and the lack of feedback make it difficult for an individual to recognize any noticeable improvements due to their own contribution. Studies of social dilemmas have shown that a simple perception of efficacy leads to increased contributions to a public good1,2. Organizations know and understand this problem. Consider an organization that pairs donors up with sponsor families. They are demonstrating  how the donor’s contributions of cents per day is actually making a difference. These systems also often incorporate other feedback, such as letters from the family or photos.

A Step Function

When the production function is a step function there may be no noticeable increase in output until a given threshold is reached. If individuals can be convinced that only a few more donations are required in order to reach that threshold research1 has demonstrated that contributions can be increased. In addition, research1 has indicated that placing individuals in groups where each player understands that their individual contributions are critical to the provision of the good increases overall contributions. The key here again is finding a way to convince individuals that their contributions matter for the success and failure of the group.

One of the tasks of the new gamification movement is to figure out how to move beyond just providing individuals with badges and achievements and instead provide an individual with a real sense of meaning. Think about the psychological payoff for getting an achievement versus making the final contribution to move to the next step on a production function. Social media and game mechanics provide us with mechanisms for breaking up projects into many small step-functions. What if I could join a Facebook group that recruits a few hundred friends to recycle their plastics, glass, and paper for a month. Imagine if feedback was provided showing how the amount donated improved air quality, saved landfill space, and made new materials. In one of his posts, James Cummings showed us how Stanford University was creating a game that promoted more efficient energy use. Hopefully this is just the tip of the iceberg, and game developers can provide insights to policy makers about how to increase meaning and efficacy to increase cooperation and reduce free riding on public goods.（source:gamasutra）