Abstract | ||
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This paper proposes a general problem-solving framework for modeling of agent negotiation via fuzzy constraint processing to acquire an optimal solution that satisfies agents in the environment of incomplete and imprecise information. In this approach, fuzzy constraint processing serves not only to improve the efficiency of the agent's individual negotiation strategy which aims at the maximal satisfaction of its self-interest, but also to represent a negotiation protocol which determines legal or meaningful sequences of messages that must be satisfied. Thus, our approach is to model agent negotiation based on fuzzy constraint processing as a distributed fuzzy constraint satisfaction problem which objective is to find a solution that has maximal satisfaction for all fuzzy constraints in the distributed environment. In this paper, we introduce the concept of fuzzy constraint processing and the definition of distributed fuzzy constraint network. Then, the approach for modeling agent negotiation via fuzzy constraint processing is presented. Next, to demonstrate the effectiveness of this approach, an example of phone-trading in electronic marketplace is provided |
Year | DOI | Venue |
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2001 | 10.1109/FUZZ.2001.1007344 | Fuzzy Systems, 2001. The 10th IEEE International Conference |
Keywords | Field | DocType |
constraint handling,fuzzy set theory,multi-agent systems,problem solving,software agents,agent negotiation,distributed fuzzy constraint satisfaction problem,fuzzy constraint processing,fuzzy modeling,imprecise information,multiple agent systems,negotiation protocol,problem-solving,software agents | Neuro-fuzzy,Computer science,Fuzzy set operations,Fuzzy logic,Fuzzy transportation,Fuzzy set,Multi-agent system,Constraint satisfaction dual problem,Artificial intelligence,Hybrid algorithm (constraint satisfaction) | Conference |
Volume | Citations | PageRank |
1 | 1 | 0.38 |
References | Authors | |
3 | 2 |
Name | Order | Citations | PageRank |
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K. Robert Lai | 1 | 263 | 26.04 |
Menq-Wen Lin | 2 | 53 | 5.23 |