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Averting the Tragedy of the Commons by Adapting Aspiration Levels

机译:通过适应愿望水平来避免公地悲剧

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The Tragedy of the Commons involves a community utiliz ing a shared resource (the "commons") which can sustain a maximum load capacity beyond which its performance degrades. If utility received is proportional to the load applied on the system, individuals will maxi mize their applied load. Such greedy behavior will eventually lead to the total load exceeding the capacity of the commons. Thereafter, individuals will get less for adding more load on the system, which signifies a social dilemma. We develop a distributed solution approach to the tragedy of the commons that require individuals in the society to adapt their aspira tions and apply loads based on their own aspirations. An aspiration level corresponds to the satisficing return for an individual, which is adjusted based on experience. In our model, individuals choose the load applied on the system based on their aspiration levels, thereby affecting the stability and performance of the "commons." We evaluate two different aspiration and load adjustment policies as well as effects of asynchronous decision making on the stability and performance of populations of varying sizes. Interesting results include mitigation of free-riding for larger populations. We also develop a mathematical model to predict the convergence time for such populations and verify the predictions experimentally.
机译:公地的悲剧涉及社区利用共享资源(“公共资源”),该资源可以维持最大负载能力,超过该负载能力其性能将下降。如果收到的效用与系统上施加的负载成比例,则个人将最大化其施加的负载。这种贪婪的行为最终将导致总负荷超过公共能力。此后,由于在系统上增加了更多的负载,个人将获得更少的利益,这表明存在社会困境。我们针对公地悲剧开发了一种分布式解决方案方法,该方法要求社会中的个人适应自己的抱负并根据自己的抱负施加负担。期望水平对应于个人的满意回报,可根据经验进行调整。在我们的模型中,个人根据自己的期望水平选择施加在系统上的负载,从而影响“常见”的稳定性和性能。我们评估了两种不同的期望和负载调整策略,以及异步决策对不同规模人口的稳定性和性能的影响。有趣的结果包括减轻了许多人的搭便车现象。我们还开发了数学模型来预测此类人群的收敛时间,并通过实验验证该预测。

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