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A neural model of bilateral negotiation consisting of one and two issues

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Author
Strand, Neil B.
Date
1990-03
Advisor
Bui, Tung X.
Second Reader
Williamson, Lawrence
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Abstract
This thesis demonstrates that neural technology may be successfully employed to mimic some of the thought process of a negotiator during a bilateral negotiation. Using the constraint satisfaction paradigm, originally developed to explore parallel distributed processing, a neural network is proposed to emulate the thought process of a buyer who negotiates the purchase of a good based on price and quality. The findings of this thesis suggest that continued research in neural networks to replicate the mental model of the negotiator holds great promise. The ability to model true beliefs and evaluation methods has an advantage over more traditionally prescriptive models. The neural network model allows incorporation of human irrationality and provides an ability to assess how that irrationality affects the negotiation outcome.
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This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.
URI
http://hdl.handle.net/10945/27160
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