{
  "annotation_id": "c727096d-78fa-4dd3-a38a-66d759e4bb3b",
  "date_created": "2026-03-02T18:01:07.271000Z",
  "date_modified": "2026-03-02T18:01:07.271000Z",
  "file_hash": "d4c3bfd81eb72af1ef7edc5676d575f9822b63783a23751a86645e3929110aa2",
  "private": false,
  "record": {
    "abstract": "The evolutionary Prisoner\u0027s Dilemma Game (PDG) and the Snowdrift Game (SG)\nwith preferential learning mechanism are studied in the Barab\\\u0027asi-Albert\nnetwork. Simulation results demonstrate that the preferential learning of\nindividuals remarkably promotes the cooperative behavior for both two games\nover a wide range of payoffs. To understand the effect of preferential learning\non the evolution of the systems, we investigate the time series of the\ncooperator density for different preferential strength and payoffs. It is found\nthat in some specific cases two games both show the $1/f$-scaling behaviors,\nwhich indicate the existence of long range correlation. We also figure out that\nwhen the large degree nodes have high probability to be selected, the PDG\ndisplays a punctuated equilibrium-type behavior. On the contrary, the SG\nexhibits a sudden increase feature. These temporary instable behaviors are\nascribed to the strategy shift of the large degree nodes.",
    "arxiv_id": "physics/0603007",
    "authors": [
      "Jie Ren",
      "Wen-Xu Wang",
      "Gang Yan",
      "Bing-Hong Wang"
    ],
    "categories": [
      "physics.soc-ph"
    ],
    "title": "Emergence of cooperation induced by preferential learning",
    "url": "https://arxiv.org/abs/physics/0603007"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "76ff4f13-0b48-4db2-a2ea-4c123fd3baa2",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}