A Similarity-Based Learning Approach for Adaptive Negotiations

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with host publication)peer-review

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Author(s)

Detail(s)

Original languageEnglish
Title of host publicationProceedings of the International Conference on Machine Learning; Models, Technologies and Applications
Pages281-287
Publication statusPublished - 2003
Externally publishedYes

Conference

TitleProceedings of the International Conference on Machine Learning; Models, Technologies and Applications, MLMTA'03
PlaceUnited States
CityLas Vegas, NV
Period23 - 26 June 2003

Abstract

Negotiation is a crucial step in the process of multi-agent decision making. Theories and techniques for automated negotiations have substantial practical values for agent-mediated electronic commerce. As a negotiation context tends to change over time, negotiation agents must be able to learn the changing contextual information (e.g., current preferences of their opponents) in order to make sensible deal acceptance decisions and to speed up the negotiation processes. Existing adaptive negotiation methods are still primitive in terms of what a negotiation agent can learn (e.g., price only) and how responsive an agent is towards the changing negotiation issues. This paper proposes a novel similarity-based learning method for adaptive negotiation agents. These agents are sensitive to multiple issues in a changing negotiation context. By observing their opponents' moves, these adaptive negotiation agents can make more sensible counter offers to speed up the negotiation processes. According to our preliminary experiment, the proposed similarity-based learning negotiation agents outperform their non-adaptive counterparts. In addition, their performance is comparable to that of the more sophisticated genetic algorithms based adaptive negotiation agents.

Research Area(s)

  • Adaptive Negotiation Agents, K-Nearest Neighbour Method, Mahalanobis distance

Citation Format(s)

A Similarity-Based Learning Approach for Adaptive Negotiations. / Lau, Raymond Y.K.
Proceedings of the International Conference on Machine Learning; Models, Technologies and Applications. 2003. p. 281-287.

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with host publication)peer-review