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Learning to play 3 x 3 games : neural networks as bounded-rational players
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Sgroi, Daniel and Zizzo, Daniel John (2009) Learning to play 3 x 3 games : neural networks as bounded-rational players. Journal of Economic Behavior and Organization, Vol.69 (No.1). pp. 27-38. doi:10.1016/j.jebo.2008.09.008 ISSN 0167-2681.
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Official URL: http://dx.doi.org/10.1016/j.jebo.2008.09.008
Abstract
We present a neural network methodology for learning game-playing rules in general. Existing research suggests learning to find a Nash equilibrium in a new game is too difficult a task for a neural network, but says little about what it will do instead. We observe that a neural network trained to find Nash equilibria in a known subset of games, will use self-taught rules developed endogenously when facing new games. These rules are close to payoff dominance and its best response. Our findings are consistent with existing experimental results, both in terms of subject's methodology and success rates.
Item Type: | Journal Article | ||||
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Subjects: | H Social Sciences > HB Economic Theory | ||||
Divisions: | Faculty of Social Sciences > Economics | ||||
Library of Congress Subject Headings (LCSH): | Noncooperative games (Mathematics), Microeconomics | ||||
Journal or Publication Title: | Journal of Economic Behavior and Organization | ||||
Publisher: | Elsevier Science BV | ||||
ISSN: | 0167-2681 | ||||
Official Date: | January 2009 | ||||
Dates: |
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Volume: | Vol.69 | ||||
Number: | No.1 | ||||
Number of Pages: | 12 | ||||
Page Range: | pp. 27-38 | ||||
DOI: | 10.1016/j.jebo.2008.09.008 | ||||
Status: | Peer Reviewed | ||||
Access rights to Published version: | Open Access (Creative Commons) | ||||
Version or Related Resource: | Sgroi, D. and Zizzo, D.J. (2007) Learning to play 3x3 games: neural networks as bounded-rational players. Cambridge: Cambridge University, Department of Economics. (Cambridge Working Papers in Economics, no. 2, 2007). | ||||
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