Evolving Ecological Social Dilemmas: A Spatial Individual-Based Model for theEvolution of Cooperation with a Minimal Number of Parameters

H. Fort
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引用次数: 1

Abstract

Cooperation, both intraspecific and interspecific, is a well-documented phenomenon in nature that is not well understood. Evolutionary game theory is a powerful tool to approach this problem. However, it has important limitations. First, very often it is not obvious which game is more appropriate to use. Second, in general, identical payoff matrices are assumed for all players, a situation that is highly unlikely in nature. Third, slight changes in these payoff values can dramatically alter the outcomes. Here, I use an evolutionary spatial model in which players do not have a universal payoff matrix, so no payoff parameters are required. Instead, each is equipped with random values for the payoffs, fulfilling the constraints that define the game(s). These payoff matrices evolve by natural selection. Two versions of this model are studied. First is a simpler one, with just one evolving payoff. Second is the “full” version, with all the four payoffs evolving. The fraction of cooperator agents converges in both versions to nonzero values. In the case of the full version, the initial heterogeneity disappears and the selected game is the “Stag Hunt.”
演化中的生态社会困境:一个基于空间个体的最小参数合作演化模型
种内和种间的合作是一种有充分记载的自然界现象,但尚未得到很好的理解。进化博弈论是解决这个问题的有力工具。然而,它有重要的局限性。首先,我们并不清楚哪种游戏更适合使用。其次,一般来说,假设所有玩家的收益矩阵都是相同的,这在本质上是极不可能的。第三,这些回报值的微小变化会极大地改变结果。在这里,我使用了一个进化空间模型,在这个模型中,玩家没有普遍的收益矩阵,所以不需要收益参数。相反,每一种都配备了随机的收益值,满足了定义游戏的约束条件。这些收益矩阵是通过自然选择进化而来的。研究了该模型的两个版本。首先是一个更简单的方法,只有一个不断变化的收益。第二种是“完整”版本,所有四种收益都在不断发展。在两个版本中,合作代理的分数收敛到非零值。在完整版本中,最初的异质性消失了,选择的游戏是“猎鹿”。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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