Cautious cooperative learning with distributed case-based reasoning

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

Abstract

In this paper, we propose a cautious cooperative learning approach using distributed case-based reasoning. Our approach consists of two learning mechanisms: individual and cooperative learning. Normally, an agent conducts individual learning to learn from its past behavior. When the agent encounters a problem that it has failed to solve (satisfactorily), it triggers cooperative learning, asking for help from its neighboring agents. To avoid corrupting its own casebase and incurring costs on itself and other agents, our agent employs an axiomatic, cautious strategy that includes the notion of a chronological casebase, a profile-based neighbor selection, and a case review and adaptation before adopting an incoming case. Here we report on the approach and some results in a real-time negotiation domain.

Original languageEnglish (US)
Title of host publicationProceedings of the Seventeenth International FloridaArtificial Intelligence Research Society Conference, FLAIRS 2004
EditorsV. Barr, Z. Markov
Pages196-201
Number of pages6
StatePublished - 2004
EventProceedings of the Seventeenth International Florida Artificial Intelligence Research Society Conference, FLAIRS 2004 - Miami Beach, FL, United States
Duration: May 17 2004May 19 2004

Publication series

NameProceedings of the Seventeenth International Florida Artificial Intelligence Research Society Conference, FLAIRS 2004
Volume1

Conference

ConferenceProceedings of the Seventeenth International Florida Artificial Intelligence Research Society Conference, FLAIRS 2004
CountryUnited States
CityMiami Beach, FL
Period5/17/045/19/04

ASJC Scopus subject areas

  • Engineering(all)

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  • Cite this

    Soh, L. K. (2004). Cautious cooperative learning with distributed case-based reasoning. In V. Barr, & Z. Markov (Eds.), Proceedings of the Seventeenth International FloridaArtificial Intelligence Research Society Conference, FLAIRS 2004 (pp. 196-201). (Proceedings of the Seventeenth International Florida Artificial Intelligence Research Society Conference, FLAIRS 2004; Vol. 1).