Aspiration-driven co-evolution of cooperation with individual behavioral diversity.

Yongqiong Yuan, Jian Wang, Zhigang Wang, Haochun Yang, Tao Xu, Huang Huang
Author Information
  1. Yongqiong Yuan: Key Laboratory of Data Link, China Electronics Technology Group Corporation, Xi'an, China.
  2. Jian Wang: AVIC Chengdu Aircraft Design & Research Institute, Chengdu, China.
  3. Zhigang Wang: Key Laboratory of Data Link, China Electronics Technology Group Corporation, Xi'an, China.
  4. Haochun Yang: School of Computer Science and Engineering, Northwestern Polytechnical University, Xi'an, Shaanxi, China. ORCID
  5. Tao Xu: School of Computer Science and Engineering, Northwestern Polytechnical University, Xi'an, Shaanxi, China.
  6. Huang Huang: School of Computer Science and Engineering, Northwestern Polytechnical University, Xi'an, Shaanxi, China.

Abstract

In evolutionary game, aspiration-driven updates and imitation updates are the two dominant game models, and individual behavior patterns are mainly categorized into two types: node player and link player. In more recent studies, the mixture strategy of different types of players has been proven to improve cooperation substantially. Motivated by such a co-evolution mechanism, we combine aspiration dynamics with individual behavioral diversity, where self-assessed aspirations are used to update imitation strategies. In this study, the node players and the link players are capable to transform into each other autonomously, which introduces new features to cooperation in a diverse population as well. In addition, by driving all the players to form specific behavior patterns, the proposed mechanism achieves a survival environment optimization of the cooperators. As expected, the interaction between node players and link players allows the cooperator to avoid the invasion of the defector. Based on the experimental evaluation, the proposed work has demonstrated that the co-evolution mechanism has facilitated the emergence of cooperation by featuring mutual transformation between different players. We hope to inspire a new way of thinking for a promising solution to social dilemmas.

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MeSH Term

Biological Coevolution
Cooperative Behavior

Word Cloud

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