Learning communication in interactive dynamic influence diagrams

Yifeng Zeng, Hua Mao, Prashant Doshi, Yinghui Pan, Jian Luo

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

2 Citations (Scopus)

Abstract

Communication is one of central activities in multiagent systems. It enables the knowledge sharing among multiple agents and improves the planning quality in a long run. In this paper, we study communication decision problems in the framework of interactive dynamic influence diagrams~(I-DIDs). I-DIDs are recognized probabilistic graphical models for sequential decision making in uncertain multiagent settings. We extend the representation to explicitly model communication actions as well as their relations to other variables in the domain. The challenging work is on developing an incentive mechanism that drives level 0 agents to learn communication while they act alone in a dynamic environment. We present solutions to the new model and show meaningful communication strategies in a multiagent problem domain.

Original languageEnglish
Title of host publicationProceedings - 2012 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, IAT 2012
Number of pages8
Volume2
PublisherIEEE
Publication date2012
Pages243-250
Article number6511577
ISBN (Print)978-0-7695-4880-7
DOIs
Publication statusPublished - 2012
Event2012 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, IAT 2012 - Macau, China
Duration: 4 Dec 20127 Dec 2012

Conference

Conference2012 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, IAT 2012
Country/TerritoryChina
CityMacau
Period04/12/201207/12/2012
SponsorIEEE

Keywords

  • agent modeling
  • communication
  • planning

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