Conflict estimation of abstract plans for multiagent systems

Toshiharu Sugawara, Satoshi Kurihara, Toshio Hirotsu, Kensuke Fukuda, Toshihiro Takada

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

Abstract

In hierarchical planning, selecting a plan at an abstract level affects planning performance because an abstract plan restricts the scope of primitive plans. However, if all primitive plans under the selected abstract plan have difficult-to-resolve conflicts with the plans of other agents, the final plan after conflict resolution will be inefficient or of low quality. In this paper, we propose a conflict estimation method to generate quality plans efficiently for multiagent systems by appropriately selecting abstract plans in hierarchical planning. This method enables agents to learn which abstract plans are less likely to cause conflicts or which conflicts will be easy to resolve.

Original languageEnglish
Title of host publicationAAMAS'07 - Proceedings of the 6th International Joint Conference on Autonomous Agents and Multiagent Systems
Pages849-851
Number of pages3
DOIs
Publication statusPublished - 2007 Dec 1
Externally publishedYes
Event6th International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS'07 - Honolulu, HI, United States
Duration: 2008 May 142008 May 18

Publication series

NameProceedings of the International Conference on Autonomous Agents

Other

Other6th International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS'07
CountryUnited States
CityHonolulu, HI
Period08/5/1408/5/18

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Keywords

  • Conflict resolution
  • Coordination
  • Planning

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence
  • Computer Networks and Communications
  • Theoretical Computer Science

Cite this

Sugawara, T., Kurihara, S., Hirotsu, T., Fukuda, K., & Takada, T. (2007). Conflict estimation of abstract plans for multiagent systems. In AAMAS'07 - Proceedings of the 6th International Joint Conference on Autonomous Agents and Multiagent Systems (pp. 849-851). [125] (Proceedings of the International Conference on Autonomous Agents). https://doi.org/10.1145/1329125.1329279