Individual planning in open and typed agent systems

Muthukumaran Chandrasekaran, Adam Eck, Prashant Doshi, Leenkiat Soh

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

16 Scopus citations

Abstract

Open agent systems are multiagent systems in which one or more agents may leave the system at any time possibly resuming after some interval and in which new agents may also join. Planning in such systems becomes challenging in the absence of inter-agent communication because agents must predict if others have left the system or new agents are now present to decide on possibly choosing a different line of action. In this paper, we prioritize open systems where agents of differing types may leave and possibly reenter but new agents do not join. With the help of a realistic domain-wildfire suppression-we motivate the need for individual planning in open environments and present a first approach for robust decision-theoretic planning in such multiagent systems. Evaluations in domain simulations clearly demonstrate the improved performance compared to previous methods that disregard the openness.

Original languageEnglish (US)
Title of host publication32nd Conference on Uncertainty in Artificial Intelligence 2016, UAI 2016
EditorsDominik Janzing, Alexander Ihler
PublisherAssociation For Uncertainty in Artificial Intelligence (AUAI)
Pages82-91
Number of pages10
ISBN (Electronic)9781510827806
StatePublished - 2016
Event32nd Conference on Uncertainty in Artificial Intelligence 2016, UAI 2016 - Jersey City, United States
Duration: Jun 25 2016Jun 29 2016

Publication series

Name32nd Conference on Uncertainty in Artificial Intelligence 2016, UAI 2016

Other

Other32nd Conference on Uncertainty in Artificial Intelligence 2016, UAI 2016
Country/TerritoryUnited States
CityJersey City
Period6/25/166/29/16

ASJC Scopus subject areas

  • Artificial Intelligence

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