Network reciprocity by coexisting learning and teaching strategies

Jun Tanimoto, Markus Brede, Atsuo Yamauchi

研究成果: Contribution to journalArticle査読

86 被引用数 (Scopus)

抄録

We propose a network reciprocity model in which an agent probabilistically adopts learning or teaching strategies. In the learning adaptation mechanism, an agent may copy a neighbor's strategy through Fermi pairwise comparison. The teaching adaptation mechanism involves an agent imposing its strategy on a neighbor. Our simulations reveal that the reciprocity is significantly affected by the frequency with which learning and teaching agents coexist in a network and by the structure of the network itself.

本文言語英語
論文番号032101
ジャーナルPhysical Review E - Statistical, Nonlinear, and Soft Matter Physics
85
3
DOI
出版ステータス出版済み - 3 21 2012

All Science Journal Classification (ASJC) codes

  • 統計物理学および非線形物理学
  • 統計学および確率
  • 凝縮系物理学

フィンガープリント

「Network reciprocity by coexisting learning and teaching strategies」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

引用スタイル