Emergence of conventions in conflict situations in complex agent network environments

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

1 Citation (Scopus)

Abstract

We modelled the conflict situation using a Markov game on various complex networks and investigated the emergence of conventions for conflict resolutions in agent networks with various structures through pairwise reinforcement learning. We found the network structure strongly affected their emergence and the agents could sometimes learn no conventions although they could learn locally consistent actions for resolutions.

Original languageEnglish
Title of host publication13th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2014
PublisherInternational Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)
Pages1459-1460
Number of pages2
ISBN (Electronic)9781634391313
Publication statusPublished - 2014 Jan 1
Event13th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2014 - Paris, France
Duration: 2014 May 52014 May 9

Publication series

Name13th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2014
Volume2

Conference

Conference13th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2014
CountryFrance
CityParis
Period14/5/514/5/9

Keywords

  • Conflict resolution
  • Conventions
  • Norms
  • Social networks

ASJC Scopus subject areas

  • Artificial Intelligence

Fingerprint Dive into the research topics of 'Emergence of conventions in conflict situations in complex agent network environments'. Together they form a unique fingerprint.

  • Cite this

    Sugawara, T. (2014). Emergence of conventions in conflict situations in complex agent network environments. In 13th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2014 (pp. 1459-1460). (13th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2014; Vol. 2). International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS).