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On Equilibrium Properties of the Replicator-Mutator Equation in Deterministic and Random Games

机译:关于确定性和随机游戏中的复制器 - 变异方程的平衡性质

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In this paper, we study the number of equilibria of the replicator-mutator dynamics for both deterministic and random multi-player two-strategy evolutionary games. For deterministic games, using Descartes' rule of signs, we provide a formula to compute the number of equilibria in multi-player games via the number of change of signs in the coefficients of a polynomial. For two-player social dilemmas (namely the Prisoner's Dilemma, Snow Drift, Stag Hunt and Harmony), we characterize (stable) equilibrium points and analytically calculate the probability of having a certain number of equilibria when the payoff entries are uniformly distributed. For multi-player random games whose pay-offs are independently distributed according to a normal distribution, by employing techniques from random polynomial theory, we compute the expected or average number of internal equilibria. In addition, we perform extensive simulations by sampling and averaging over a large number of possible payoff matrices to compare with and illustrate analytical results. Numerical simulations also suggest several interesting behaviours of the average number of equilibria when the number of players is sufficiently large or when the mutation is sufficiently small. In general, we observe that introducing mutation results in a larger average number of internal equilibria than when mutation is absent, implying that mutation leads to larger behavioural diversity in dynamical systems. Interestingly, this number is largest when mutation is rare rather than when it is frequent.
机译:在本文中,我们研究了对确定性和随机多人双策略进化游戏的复制器 - 突变动力学的均衡数量。对于确定性游戏,使用Descartes的符号规则,我们提供了通过多项式系数的系数中的符号的变化数来计算多人游戏的均衡数量的公式。对于双人的社交困境(即囚犯的困境,雪漂,Stag Hunt和Harmony),我们表征(稳定)均衡点,并在支付条目均匀分布时分析计算具有一定数量的均衡的可能性。对于多人随机游戏,通过采用随机多项式理论的使用技术来独立分布,其降低自主分布,我们计算内部均衡的预期或平均数量。此外,我们通过采样和平均大量可能的收益矩阵来执行广泛的模拟,以比较和说明分析结果。数值模拟还提出了当玩家的数量足够大或当突变足够小时的平均均衡数量的几个有趣行为。通常,我们观察到,引入突变导致比不存在突变的较大平均内部均衡数量,这意味着突变导致动力系统中的较大行为多样性。有趣的是,当突变是罕见的而不是频繁时,这个数字是最大的。

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