Decision theoretic norm-governed planning

Luca Gasparini, Timothy J. Norman, Martin J. Kollingbaum, Liang Chen

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

2 Citations (Scopus)

Abstract

We propose Normative Dec-POMDPs, a model of collective decision making in the presence of complex norms, with violations of norms classified according to their relative severity. We extend the PBPG algorithm in order to solve Normative Dec-POMDPs and propose a heuristic that improves its scalability without affecting the policy quality.

Original languageEnglish
Title of host publicationAAMAS '16 International Conference on Agents and Multiagent Systems
Place of PublicationRichland, SC
PublisherInternational Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)
Pages1265-1266
Number of pages2
ISBN (Electronic)9781450342391
Publication statusPublished - 2016
Event15th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2016 - Singapore, Singapore
Duration: 9 May 201613 May 2016

Conference

Conference15th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2016
CountrySingapore
CitySingapore
Period9/05/1613/05/16

Keywords

  • Coordination
  • Decision theory
  • Norms

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  • Cite this

    Gasparini, L., Norman, T. J., Kollingbaum, M. J., & Chen, L. (2016). Decision theoretic norm-governed planning. In AAMAS '16 International Conference on Agents and Multiagent Systems (pp. 1265-1266). International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS).