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多智能体运动交互中的纳什均衡

Nash equilibria in multi-agent motor interactions.

作者信息

Braun Daniel A, Ortega Pedro A, Wolpert Daniel M

机构信息

Computational and Biological Learning Laboratory, Department of Engineering, University of Cambridge, Cambridge, UK.

出版信息

PLoS Comput Biol. 2009 Aug;5(8):e1000468. doi: 10.1371/journal.pcbi.1000468. Epub 2009 Aug 14.

Abstract

Social interactions in classic cognitive games like the ultimatum game or the prisoner's dilemma typically lead to Nash equilibria when multiple competitive decision makers with perfect knowledge select optimal strategies. However, in evolutionary game theory it has been shown that Nash equilibria can also arise as attractors in dynamical systems that can describe, for example, the population dynamics of microorganisms. Similar to such evolutionary dynamics, we find that Nash equilibria arise naturally in motor interactions in which players vie for control and try to minimize effort. When confronted with sensorimotor interaction tasks that correspond to the classical prisoner's dilemma and the rope-pulling game, two-player motor interactions led predominantly to Nash solutions. In contrast, when a single player took both roles, playing the sensorimotor game bimanually, cooperative solutions were found. Our methodology opens up a new avenue for the study of human motor interactions within a game theoretic framework, suggesting that the coupling of motor systems can lead to game theoretic solutions.

摘要

在诸如最后通牒博弈或囚徒困境等经典认知博弈中,当多个拥有完备信息的竞争性决策者选择最优策略时,社会互动通常会导致纳什均衡。然而,在进化博弈理论中,已经证明纳什均衡也可以作为动态系统中的吸引子出现,例如可以描述微生物的种群动态。与这种进化动态类似,我们发现纳什均衡在玩家争夺控制权并试图最小化努力的运动互动中自然出现。当面对与经典囚徒困境和拔河游戏相对应的感觉运动互动任务时,两人的运动互动主要导致纳什解。相比之下,当单个玩家同时扮演两个角色,双手进行感觉运动游戏时,则会出现合作解。我们的方法为在博弈论框架内研究人类运动互动开辟了一条新途径,表明运动系统的耦合可以导致博弈论解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f0f1/2714462/b9744b19c9b5/pcbi.1000468.g001.jpg

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