英文标题：
《Self-organization in a distributed coordination game through heuristic
  rules》
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作者：
S. Agarwal, D. Ghosh and A. S. Chakrabarti
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最新提交年份：
2016
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英文摘要：
  In this paper we consider a distributed coordination game played by a large number of agents with finite information sets, which characterizes emergence of a single dominant attribute out of a large number of competitors. Formally, $N$ agents play a coordination game repeatedly which has exactly $N$ Nash equilibria and all of the equilibria are equally preferred by the agents. The problem is to select one equilibrium out of $N$ possible equilibria in the least number of attempts. We propose a number of heuristic rules based on reinforcement learning to solve the coordination problem. We see that the agents self-organize into clusters with varying intensities depending on the heuristic rule applied although all clusters but one are transitory in most cases. Finally, we characterize a trade-off in terms of the time requirement to achieve a degree of stability in strategies and the efficiency of such a solution.
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中文摘要：
在本文中，我们考虑了一个由大量具有有限信息集的代理参与的分布式协调博弈，其特征是大量竞争对手中出现了一个单一的主导属性。形式上，$N$代理重复地玩一个协调博弈，该博弈具有精确的$N$纳什均衡，并且所有均衡都是代理同样偏好的。问题是要以最少的尝试次数从$N$可能的均衡中选择一个均衡。我们提出了一些基于强化学习的启发式规则来解决协调问题。我们发现，尽管在大多数情况下，除一个簇外，所有簇都是暂时的，但代理会根据应用的启发式规则以不同的强度自组织成簇。最后，我们描述了在时间要求方面的权衡，以实现策略的一定程度的稳定性和这种解决方案的效率。
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分类信息：

一级分类：Quantitative Finance        数量金融学
二级分类：Economics        经济学
分类描述：q-fin.EC is an alias for econ.GN. Economics, including micro and macro economics, international economics, theory of the firm, labor economics, and other economic topics outside finance
q-fin.ec是econ.gn的别名。经济学，包括微观和宏观经济学、国际经济学、企业理论、劳动经济学和其他金融以外的经济专题
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