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The Design and Implementation of an Intelligent Agent-Based Adaptive Bargaining Model (ABM)

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Knowledge-Based Intelligent Information and Engineering Systems (KES 2005)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3681))

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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.

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© 2005 Springer-Verlag Berlin Heidelberg

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Mak, R.Y.W., Lee, R.S.T. (2005). The Design and Implementation of an Intelligent Agent-Based Adaptive Bargaining Model (ABM). In: Khosla, R., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2005. Lecture Notes in Computer Science(), vol 3681. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11552413_97

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  • DOI: https://doi.org/10.1007/11552413_97

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28894-7

  • Online ISBN: 978-3-540-31983-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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