Coordinated exploration in conflicting multi-stage games

Maarten Peeters, Ville Könönen, Katja Verbeeck, Sven van Segbroeck, Ann Nowé

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review


The analysis of the collective behavior of agents in a distributed multi-agent environment received a lot of attention in the past decade. More accurately, coordination was studied intensely because it enables agents to converge to Pareto optimal solutions and Nash equilibria. Most of these studies focussed on team games. In this paper we report on a technique for finding fair solutions in conflicting interest multi-stage games. Our hierarchical periodic policies algorithm is based on the characteristics of a homo egualis society in which the players also care about the proportional distribution of the pay-off in relation to the pay-off of the other players. This feature is built into a hierarchy of learning automata which is suited for playing sequential decision problems.
Original languageEnglish
Title of host publicationKnowledge-Based Intelligent Information and Engineering Systems
Subtitle of host publication12th International Conference, KES 2008
EditorsIgnic Lovrek, Robert J. Howlett, Lakhmi C. Jain
Place of PublicationHeidelberg
ISBN (Print)978-3-540-85564-4
Publication statusPublished - 2008
MoE publication typeA4 Article in a conference publication
Event12th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES-2008 - Zagreb, Croatia
Duration: 3 Sept 20085 Sept 2008
Conference number: 12

Publication series

SeriesLecture Notes in Computer Science


Conference12th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES-2008
Abbreviated titleKES-2008


  • Learning automata
  • reinforcement learning
  • policy gradient
  • multi-agent systems
  • exploration


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