dorsal/arxiv
View SchemaEvolutionary Markovian Strategies in 2 x 2 Spatial Games
| Authors | Hugo Fort, Estrella Sicardi |
|---|---|
| Categories | |
| ArXiv ID | physics/0606076 |
| URL | https://arxiv.org/abs/physics/0606076 |
| DOI | 10.1016/j.physa.2006.09.004 |
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 parameteres. Each agent is governed by a binary Markovian strategy (BMS) specified by 4 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 2^4= 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 stochastichally); and iii) the amount of noise measured by a parameter epsilon. However a robust winner strategy is [1,0,1,1].
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"abstract": "Evolutionary spatial 2 x 2 games between heterogeneous agents are analyzed\nusing different variants of cellular automata (CA). Agents play repeatedly\nagainst their nearest neighbors 2 x 2 games specified by a rescaled payoff\nmatrix with two parameteres. Each agent is governed by a binary Markovian\nstrategy (BMS) specified by 4 conditional probabilities [p_R, p_S, p_T, p_P]\nthat take values 0 or 1. The initial configuration consists in a random\nassignment of \"strategists\" among the 2^4= 16 possible BMS. The system then\nevolves within strategy space according to the simple standard rule: each agent\ncopies the strategy of the neighbor who got the highest payoff. Besides on the\npayoff matrix, the dominant strategy -and the degree of cooperation- depend on\ni) the type of the neighborhood (von Neumann or Moore); ii) the way the\ncooperation state is actualized (deterministically or stochastichally); and\niii) the amount of noise measured by a parameter epsilon. However a robust\nwinner strategy is [1,0,1,1].",
"arxiv_id": "physics/0606076",
"authors": [
"Hugo Fort",
"Estrella Sicardi"
],
"categories": [
"physics.soc-ph"
],
"doi": "10.1016/j.physa.2006.09.004",
"title": "Evolutionary Markovian Strategies in 2 x 2 Spatial Games",
"url": "https://arxiv.org/abs/physics/0606076"
},
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