Markov Chains of Evolutionary Games with a Small Number of Players
Fuente:
arXiv
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| Formato: | Preprint |
| Publicado: |
2025
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| _version_ | 1866908427613110272 |
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| author | Kehagias, Athanasios |
| author_facet | Kehagias, Athanasios |
| contents | We construct and study the transition probability matrix of evolutionary games in which the number of players is finite (and relatively small) of such games. We use a simplified version of the population games studied by Sandholm. After laying out a general framework we concentrate on specific examples, involving the Iterated Prisoner's Dilemma, the Iterated Stag Hunt, and the Rock-Paper-Scissors game. Also we consider several revision protocols: Best Response, Pairwise Comparison, Pairwise Proportional Comparison etc. For each of these we explicitly construct the MC transition probability matrix and study its properties. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2506_23134 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Markov Chains of Evolutionary Games with a Small Number of Players Kehagias, Athanasios Computer Science and Game Theory Optimization and Control We construct and study the transition probability matrix of evolutionary games in which the number of players is finite (and relatively small) of such games. We use a simplified version of the population games studied by Sandholm. After laying out a general framework we concentrate on specific examples, involving the Iterated Prisoner's Dilemma, the Iterated Stag Hunt, and the Rock-Paper-Scissors game. Also we consider several revision protocols: Best Response, Pairwise Comparison, Pairwise Proportional Comparison etc. For each of these we explicitly construct the MC transition probability matrix and study its properties. |
| title | Markov Chains of Evolutionary Games with a Small Number of Players |
| topic | Computer Science and Game Theory Optimization and Control |
| url | https://arxiv.org/abs/2506.23134 |