A co-evolutionary model combined mixed-strategy and network adaptation by severing disassortative neighbors promotes cooperation in prisoner's dilemma games. (February 2021)

• Record Type: Journal Article
• Authors: Miyaji, Kohei; Tanimoto, Jun
• Is Part Of: Chaos, solitons and fractals. Volume 143(2021)
• Publication Date: 2021-02
• Subjects: Mixed-strategy -- Prisoner's dilemma -- Co-evolution -- Assortativity -- Complex Network; Chaotic behavior in systems -- Periodicals; Solitons -- Periodicals; Fractals -- Periodicals; Chaotic behavior in systems; Fractals; Solitons; Periodicals; 003.7
• DOI: 10.1016/j.chaos.2020.110603
• Languages: English
• ISSNs: 0960-0779

Abstract

Highlights: The "assortative grouping" framework enhances cooperation in the dynamic network. When a low network adaptation speed and a certain degree of strategy copy error are presumed, phenomenal network heterogeneity evolves. Abstract: 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.