An Evolutionary Trade Network Game With Preferential Partner Selection
Abstract
An evolutionary trade network game (TNG) is proposed for studying the interplay between evolutionary game dynamics and preferential partner selection in various market contexts with distributed adaptive agents. The modular form of the TNG facilitates experimentation with alternative specifications for trade partner matching, trading, expectation up dating, and trade strategy evolution. Experimental results obtained using a C++ implementation suggest that the conventional optimality properties used to evaluate agent matching mechanisms in static market contexts maybe inadequate measures of optimality from an evolutionary perspective.Download Info
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Paper provided by Iowa State University Department of Economics in its series Economic Report with number 38.Length:
Date of creation: Feb 1996
Date of revision:
Handle: RePEc:isu:iowaer:38
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Postal: Iowa State University, Dept. of Economics, 260 Heady Hall, Ames, IA 50011-1070
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Fax: +1 515.294.0221
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Web page: http://www.econ.iastate.edu
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Keywords:Other versions of this item:
- Tesfatsion, Leigh, 1996. "An Evolutionary Trade Network Game with Preferential Partner Selection," Staff General Research Papers 2047, Iowa State University, Department of Economics.
- Leigh S. Tesfatsion, . "An Evolutionary Trade Network Game with Preferential Partner Selection," Computing in Economics and Finance 1996 _057, Society for Computational Economics.
- B4 - Schools of Economic Thought and Methodology - - Economic Methodology
- C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
- C7 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory
- D2 - Microeconomics - - Production and Organizations
- D4 - Microeconomics - - Market Structure and Pricing
- D8 - Microeconomics - - Information, Knowledge, and Uncertainty
References
References listed on IDEASPlease report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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Staff General Research Papers
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Game Theory and Information
9501002, EconWPA, revised 20 Jan 1995.
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