Evolutionary Markovian strategies in 2 x 2 spatial games

Authored by H. Fort, E. Sicardi

Date Published: 2007-02-15

DOI: 10.1016/j.physa.2006.09.004

Sponsors: No sponsors listed

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Model Documentation: Other Narrative

Model Code URLs: Model code not found

Abstract

Evolutionary spatial 2 x 2 games between heterogeneous agents are analyzed using different variants of cellular automata (CA). Agents play repeatedly against their nearest neighbors 2 x 2 games specified by a rescaled payoff matrix with two parameters. Each agent is governed by a binary Markovian strategy (BMS) specified by four conditional probabilities [p(R), p(S), p(T), p(P)] that take values 0 or 1. The initial configuration consists in a random assignment of “strategists” among the 24 = 16 possible BMS. The system then evolves within strategy space according to the simple standard rule: each agent copies the strategy of the neighbor who got the highest payoff. Besides on the payoff matrix, the dominant strategy-and the degree of cooperation-depend on (i) the type of the neighborhood (von Neumann or Moore); (ii) the way the cooperation state is actualized (deterministically or stochastically); and (iii) the amount of noise measured by a parameter F. However a robust winner strategy is [1,0,1,1]. (c) 2006 Elsevier B.V. All rights reserved.

Tags

Agent-based models Complex adaptive systems Evolutionary game theory