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Output details

11 - Computer Science and Informatics

University of Kent

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Output 41 of 117 in the submission

Article title

Evolving Fuzzy Rules for Relaxed-Criteria Negotiation

Type

D - Journal article

DOI

10.1109/TSMCB.2008.928210

Title of journal

IEEE Transactions on Systems, Man, and Cybernetics—Part B: Cybernetics

Article number

Volume number

Issue number

First page of article

1486

ISSN of journal

1083-4419

Year of publication

2008

URL

Number of additional authors

Additional information

<22> This work was published in a top IEEE Journal (acceptance rate:7%). Whereas existing works on negotiation in simpler market settings focused only on optimizing utilities, this work introduced a new branch of thinking for solving much more difficult negotiation problems by devising negotiation agents that use heuristics to improve success rates and negotiation speed and can evolve their structures by learning new fuzzy rules. Favorable empirical results validated that self-evolving agents improve their negotiation outcomes as they participate in negotiations in more e-markets. It led to work by other groups (e.g., BeijingUTech) on evolving optimized parameters of fuzzy rules.

Interdisciplinary

Cross-referral requested

Research group

F - Future Computing Group

Citation count

Proposed double-weighted

Double-weighted statement

Reserve for a double-weighted output

Non-English

English abstract