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首页> 外文期刊>Chaos, Solitons and Fractals: Applications in Science and Engineering: An Interdisciplinary Journal of Nonlinear Science >A co-evolutionary model combined mixed-strategy and network adaptation by severing disassortative neighbors promotes cooperation in prisoner's dilemma games
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A co-evolutionary model combined mixed-strategy and network adaptation by severing disassortative neighbors promotes cooperation in prisoner's dilemma games

机译:共同进化模型联合混合策略和通过切割衡索邻国的网络适应促进囚犯困境游戏中的合作

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摘要

A co-evolutionary model of both network and mixed strategy is proposed in this study. The assigned strategy s(i) of agent i is defined by a real number ranging from 0 to 1, which probabilistically ordains a subsequent action of either cooperation or defection as the agent's offer. We assume a network dynamic to support or hamper the enhancement of cooperation, where an agent severs a link with the neighbor who has the most disassortative strategy. This means that an agent tends to maintain interactions only with neighbors that resemble the agent. A series of numerical simulations reveal that our "assortative grouping" framework enhances cooperation. Interestingly, when a low network adaptation speed and a certain degree of strategy copy error are presumed, phenomenal network heterogeneity evolves, one that realizes more significant cooperation as compared to error-free cases. (C) 2020 Elsevier Ltd. All rights reserved.
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