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arXiv 1405.3296cs.GT
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算法实例游戏

Algorithm Instance Games

Samuel D. Johnson, Tsai-Ching Lu

摘要:

本文介绍了算法实例游戏(AIGs)作为一个概念分类适用于游戏的结果,从联合战略的算法解决。对于这样的游戏,一个基本的问题是:算法描述的细节如何影响代理人的策略行为?我们分析了两个版本的AIG的集合覆盖优化问题的基础上。在这些游戏中,联合策略对应于集合覆盖问题的实例,每个子集(给定的元素论域)代表单个代理的策略。结果是由集合覆盖算法从联合策略计算的覆盖。在这个游戏的一个变体中,结果由确定性贪心算法计算,而另一个变体利用非确定性形式的贪心算法。我们的特点纳什均衡策略的两个版本的游戏,发现代理人的策略可以有很大的不同,在两个设置之间。特别是,我们发现基于确定性算法的游戏版本只允许代理选择策略的纳什均衡(即,子集),最多包含一个元素,没有两个代理选择相同的元素。另一方面,在基于非确定性算法的博弈版本中,纳什均衡策略可以包括具有零个、一个或每个元素的代理,并且相同的元素可以出现在多个代理的策略中。

英文摘要:

This paper introduces algorithm instance games (AIGs) as a conceptual classification applying to games in which outcomes are resolved from joint strategies algorithmically. For such games, a fundamental question asks: How do the details of the algorithm's description influence agents' strategic behavior? We analyze two versions of an AIG based on the set-cover optimization problem. In these games, joint strategies correspond to instances of the set-cover problem, with each subset (of a given universe of elements) representing the strategy of a single agent. Outcomes are covers computed from the joint strategies by a set-cover algorithm. In one variant of this game, outcomes are computed by a deterministic greedy algorithm, and the other variant utilizes a non-deterministic form of the greedy algorithm. We characterize Nash equilibrium strategies for both versions of the game, finding that agents' strategies can vary considerably between the two settings. In particular, we find that the version of the game based on the deterministic algorithm only admits Nash equilibrium in which agents choose strategies (i.e., subsets) containing at most one element, with no two agents picking the same element. On the other hand, in the version of the game based on the non-deterministic algorithm, Nash equilibrium strategies can include agents with zero, one, or every element, and the same element can appear in the strategies of multiple agents.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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