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Stochastic Evolution of Rules for Playing Finite Normal Form Games

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  • Fabrizio Germano

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Abstract

The evolution of boundedly rational rules for playing normal form games is studied within stationary environments of stochastically changing games. Rules are viewed as algorithms prescribing strategies for the different normal form games that arise. It is shown that many of the “folk resultsâ€\x9D of evolutionary game theory, typically obtained with a fixed game and fixed strategies, carry over to the present environments. The results are also related to some recent experiments on rules and games. Copyright Springer Science+Business Media, LLC 2007

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File URL: http://hdl.handle.net/10.1007/s11238-007-9032-8
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Bibliographic Info

Article provided by Springer in its journal Theory and Decision.

Volume (Year): 62 (2007)
Issue (Month): 4 (May)
Pages: 311-333

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Handle: RePEc:kap:theord:v:62:y:2007:i:4:p:311-333

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Web page: http://www.springerlink.com/link.asp?id=100341

Related research

Keywords: bounded rationality; evolutionary dynamics; learning; normal form games; rules; stochastic dynamics; C72; C73; D81; D83;

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References

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Cited by:
  1. Schipper, Burkhard C, 2008. "On an Evolutionary Foundation of Neuroeconomics," MPRA Paper 8884, University Library of Munich, Germany.
  2. Friederike Mengel, 2007. "Learning Across Games," Working Papers. Serie AD 2007-05, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
  3. Spiliopoulos, Leonidas, 2009. "Neural networks as a learning paradigm for general normal form games," MPRA Paper 16765, University Library of Munich, Germany.
  4. Spiliopoulos, Leonidas, 2012. "Interactive learning in 2×2 normal form games by neural network agents," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(22), pages 5557-5562.
  5. Rabah Amir & Igor Evstigneev & Klaus Schenk-Hoppé, 2013. "Asset market games of survival: a synthesis of evolutionary and dynamic games," Annals of Finance, Springer, vol. 9(2), pages 121-144, May.

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