进化博弈动力学中的对抗调度
Adversarial Scheduling in Evolutionary Game Dynamics
摘要：
考虑一个系统，在该系统中，底层图G的节点上的参与者反复与他们的邻居玩囚徒困境。玩家根据对手过去的行为调整策略，采用所谓的赢-留-输-转移策略。在（Kittock 94）、（Dyer等人，2002）、（Mossel和Roch，2006）中研究了这种动力学。在随机调度的情况下，从任何初始配置开始，系统都有很高的概率到达所有参与者合作的唯一固定点。本文研究了这一结果的有效性下的各种类的对抗性决策者。我们的研究结果可以概括如下：1.可以选择游戏参与者的对抗调度器可以阻止系统到达大多数图拓扑上的唯一固定点。2.只允许选择一个参与者的非自适应调度器并不比随机调度器更强大。有了这个限制，即使是自适应调度器也不会比随机调度器更强大，只要它是“合理公平的”。结果证明了我们提出的对抗性调度方法是社会科学生成方法的基础（Epstein 2007）。
英文摘要：
Consider a system in which players at nodes of an underlying graph G repeatedly play Prisoner's Dilemma against their neighbors. The players adapt their strategies based on the past behavior of their opponents by applying the so-called win-stay lose-shift strategy. This dynamics has been studied in (Kittock 94), (Dyer et al. 2002), (Mossel and Roch, 2006). With random scheduling, starting from any initial configuration with high probability the system reaches the unique fixed point in which all players cooperate. This paper investigates the validity of this result under various classes of adversarial schedulers. Our results can be sumarized as follows: 1. An adversarial scheduler that can select both participants to the game can preclude the system from reaching the unique fixed point on most graph topologies. 2. A nonadaptive scheduler that is only allowed to choose one of the participants is no more powerful than a random scheduler. With this restriction even an adaptive scheduler is not significantly more powerful than the random scheduler, provided it is "reasonably fair". The results exemplify the adversarial scheduling approach we propose as a foundational basis for the generative approach to social science (Epstein 2007).
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。
