Dynamic aspiration based on Win-Stay-Lose-Learn rule in Spatial Prisoner's Dilemma Gam
Zhenyu Shi, Wei Wei, Xiangnan Feng, Xing Li, Zhiming Zheng

TL;DR
This paper introduces a dynamic aspiration model based on Win-Stay-Lose-Learn in the spatial Prisoner's Dilemma, showing how aspiration influenced by payoffs affects cooperation and defection dynamics.
Contribution
It proposes a novel dynamic aspiration framework grounded in psychological theories, enhancing understanding of evolution in spatial Prisoner's Dilemma games.
Findings
Dynamic aspiration significantly influences evolutionary outcomes.
Different initial aspirations lead to stable coexistence, dependence, or defection explosion.
Analysis of local structures explains cooperator survival and defector expansion.
Abstract
Prisoner's dilemma game is the most commonly used model of spatial evolutionary game which is considered as a paradigm to portray competition among selfish individuals. In recent years, Win-Stay-Lose-Learn, a strategy updating rule base on aspiration, has been proved to be an effective model to promote cooperation in spatial prisoner's dilemma game, which leads aspiration to receive lots of attention. But in many research the assumption that individual's aspiration is fixed is inconsistent with recent results from psychology. In this paper, according to Expected Value Theory and Achievement Motivation Theory, we propose a dynamic aspiration model based on Win-Stay-Lose-Learn rule in which individual's aspiration is inspired by its payoff. It is found that dynamic aspiration has a significant impact on the evolution process, and different initial aspirations lead to different results,…
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