Robust spread of cooperation by expectation-of-cooperation strategy with simple labeling method

Tomoaki Otsuka, Toshiharu Sugawara

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

This paper proposes an interaction strategy called the extended expectation-of-cooperation (EEoC) that is intended to spread cooperative activities in prisoner's dilemma situations over an entire agent network. Recently developed computer and communications applications run on the network and interact with each other as delegates of the owners, so they often encounter social dilemma situations. To improve social efficiency, they are required to cooperate, but one-sided cooperation is meaningless and loses some payoff due to a rip-off by defecting agents. The concept of EEoC is that when agents encounter mutual cooperation, they continue to cooperate a few times with the desire to see the emergence of cooperative behavior in their neighbors. EEoC is easy to implement in computer systems.We experimentally show that EEoC can effectively spread cooperative activities in dilemma situations in complete, Erdös-Rényi, and regular networks. We also clarify the robustness against defecting agents and the limitation of the EEoC strategy.

Original languageEnglish
Title of host publicationProceedings - 2017 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2017
PublisherAssociation for Computing Machinery, Inc
Pages483-490
Number of pages8
ISBN (Electronic)9781450349512
DOIs
Publication statusPublished - 2017 Aug 23
Event16th IEEE/WIC/ACM International Conference on Web Intelligence, WI 2017 - Leipzig, Germany
Duration: 2017 Aug 232017 Aug 26

Publication series

NameProceedings - 2017 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2017

Other

Other16th IEEE/WIC/ACM International Conference on Web Intelligence, WI 2017
Country/TerritoryGermany
CityLeipzig
Period17/8/2317/8/26

Keywords

  • Agent network
  • Cooperation
  • Prisoner's dilemma
  • Reinforcement learning

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Artificial Intelligence
  • Software

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