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Title: The design and implementation of an intelligent agent-based adaptive bargaining model (ABM)
Authors: Mak, RYW 
Lee, RST 
Issue Date: 2005
Publisher: Springer
Source: Lecture notes in computer science (including subseries Lecture notes in artificial intelligence and lecture notes in bioinformatics), 2005, v. 3681 LNCS, no. , p. 678-685 How to cite?
Journal: Lecture notes in computer science (including subseries Lecture notes in artificial intelligence and lecture notes in bioinformatics) 
Abstract: In this paper we propose a highly adaptive bargaining model for agent shopping which stimulates two major human bargaining strategies: 1) Payoff-Oriented Strategy and 2) Real-time Adaptive Attitude Switching Strategy. Payoff-Oriented Strategy adjusts the rate of concession by determining the current payoff gained and the eagerness of the adopted attitude at each bargaining round. Also, the buying agent in this work is guided by the Real-time Adaptive Attitude Switching Strategy which comprises a set of attitude switching rules. These rules guide the buying agent to gain higher payoff and prohibit seller from gaining too much payoff. Owing to the substantial experimental results in this work, the two human-like bargaining strategies achieved the adaptive changing eagerness of a particular attitude and adaptive switching attitude in reacting to the opponent’s feedback.
Description: International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2005, 14-16 September 2005, Melbourne, VIC, Australia
ISSN: 0302-9743
EISSN: 1611-3349
DOI: 10.1007/11552413_97
Appears in Collections:Conference Paper

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