Paper Info
Title
Modeling opponent's beliefs via fuzzy constraint-directed approach in agent negotiation
Abstract
This work adopted the fuzzy constraint-directed approach to model opponent's beliefs in agent negotiation. The fuzzy constraint-directed approach involves the fuzzy probability constraint and the fuzzy instance reasoning. The fuzzy probability constraint is used to cluster the opponent's regularities and to eliminate the noisy hypotheses or beliefs, so as to increase the efficiency on the convergence of behavior patterns and to improve the effectiveness on beliefs learning. The fuzzy instance reasoning reuses the prior opponent knowledge to speed up problem-solving, and reason the proximate regularities to acquire desirable results on predicting opponent behavior. Besides, the proposed interaction method allows the agent to make a concession dynamically based on desirable objectives. Moreover, experimental results suggest that the proposed framework enabled an agent to achieve a higher reward, a fairer deal, or a less cost of negotiation.
Year
DOI
Venue
2007
10.1007/978-3-540-74171-8_17
ICIC (1)
Keywords
Field
DocType
desirable result,model opponent,fuzzy probability constraint,behavior pattern,agent negotiation,opponent behavior,fuzzy instance reasoning,prior opponent knowledge,desirable objective,fuzzy constraint-directed approach,multi agent system
Convergence (routing),Fuzzy constraint,Neuro-fuzzy,Computer science,Fuzzy logic,Multi-agent system,Artificial intelligence,Adversary,Machine learning,Speedup,Negotiation
Conference
Volume
ISSN
ISBN
4681
0302-9743
3-540-74170-4
Citations 
PageRank 
References 
0
0.34
16
Authors
4
Name
Order
Citations
PageRank
Ting Jung Yu1192.75
K. Robert Lai226326.04
Menq-Wen Lin3535.23
Bo-Ruei Kao4273.52