A Learning-Based Coalition Formation Model for Multiagent Systems

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

4 Citations (Scopus)

Abstract

In this paper, we present a learning-based coalition formation model that forms sub-optimal coalitions among agents to solve real-time constrained allocation problems in a dynamic, uncertain and noisy environment. This model consists of three stages (coalition planning, coalition instantiation and coalition evaluation) and an integrated learning framework. An agent first derives a coalition formation plan via case-based reasoning (CBR). Guided by this plan, the agent instantiates a coalition through negotiations with other agents. When the process completes, the agent evaluates the outcomes. The integrated learning framework involves multiple levels embedded in the three stages. At a low level on strategic and tactical details, the model allows an agent to learn how to negotiate. At the meta-level, an agent learns how to improve on its planning and the actual execution of the plan. The model uses an approach that synthesizes reinforcement learning (RL) and case-based learning (CBL). We have implemented the model partially and conducted experiments on CPU allocation in a multisensor target-tracking domain.

Original languageEnglish (US)
Title of host publicationProceedings of the Interantional Conference on Autonomous Agents
EditorsJ.S. Rosenschein, T. Sandholm, M. Wooldridge, M. Yakoo
Pages1120-1121
Number of pages2
Volume2
StatePublished - 2003
EventProceedings of the Second International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS 03 - Melbourne, Vic.
Duration: Jul 14 2003Jul 18 2003

Other

OtherProceedings of the Second International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS 03
CityMelbourne, Vic.
Period7/14/037/18/03

Fingerprint

Multi agent systems
Planning
Case based reasoning
Reinforcement learning
Target tracking
Program processors
Experiments

Keywords

  • Coalition formation
  • Learning
  • Multiagent systems
  • Negotiation
  • Real time

ASJC Scopus subject areas

  • Engineering(all)

Cite this

Soh, L-K., & Li, X. (2003). A Learning-Based Coalition Formation Model for Multiagent Systems. In J. S. Rosenschein, T. Sandholm, M. Wooldridge, & M. Yakoo (Eds.), Proceedings of the Interantional Conference on Autonomous Agents (Vol. 2, pp. 1120-1121)

A Learning-Based Coalition Formation Model for Multiagent Systems. / Soh, Leen-Kiat; Li, Xin.

Proceedings of the Interantional Conference on Autonomous Agents. ed. / J.S. Rosenschein; T. Sandholm; M. Wooldridge; M. Yakoo. Vol. 2 2003. p. 1120-1121.

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

Soh, L-K & Li, X 2003, A Learning-Based Coalition Formation Model for Multiagent Systems. in JS Rosenschein, T Sandholm, M Wooldridge & M Yakoo (eds), Proceedings of the Interantional Conference on Autonomous Agents. vol. 2, pp. 1120-1121, Proceedings of the Second International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS 03, Melbourne, Vic., 7/14/03.
Soh L-K, Li X. A Learning-Based Coalition Formation Model for Multiagent Systems. In Rosenschein JS, Sandholm T, Wooldridge M, Yakoo M, editors, Proceedings of the Interantional Conference on Autonomous Agents. Vol. 2. 2003. p. 1120-1121
Soh, Leen-Kiat ; Li, Xin. / A Learning-Based Coalition Formation Model for Multiagent Systems. Proceedings of the Interantional Conference on Autonomous Agents. editor / J.S. Rosenschein ; T. Sandholm ; M. Wooldridge ; M. Yakoo. Vol. 2 2003. pp. 1120-1121
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