Reinforcement learning account of network reciprocity

Takahiro Ezaki, Naoki Masuda*

*この研究の対応する著者

研究成果: Article査読

7 被引用数 (Scopus)

抄録

Evolutionary game theory predicts that cooperation in social dilemma games is promoted when agents are connected as a network. However, when networks are fixed over time, humans do not necessarily show enhanced mutual cooperation. Here we show that reinforcement learning (specifically, the so-called Bush-Mosteller model) approximately explains the experimentally observed network reciprocity and the lack thereof in a parameter region spanned by the benefit-to-cost ratio and the node’s degree. Thus, we significantly extend previously obtained numerical results.

本文言語English
論文番号e0189220
ジャーナルPloS one
12
12
DOI
出版ステータスPublished - 2017 12
外部発表はい

ASJC Scopus subject areas

  • 生化学、遺伝学、分子生物学(全般)
  • 農業および生物科学(全般)
  • 一般

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