{
  "annotation_id": "ddc6d195-2831-4ac6-be49-7398f7c999d8",
  "date_created": "2026-03-02T18:01:10.129000Z",
  "date_modified": "2026-03-02T18:01:10.129000Z",
  "file_hash": "d5e55632e3411f243e25c00d9ea29e926d75ae611d84748c925c779406811b45",
  "private": false,
  "record": {
    "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"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "5c0b449e-9e30-40e8-850a-8040f2a7cf55",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}