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Learning Across Games

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  • Friederike Mengel

    ()
    (Universidad de Alicante)

Abstract

In this paper (reinforcement) learning of decision makers that face many different games is studied. As learning separately for all games can be too costly (require too much reasoning resources) agents are assumed to partition the set of all games into analogy classes. Partitions of higher cardinality are more costly. A process of simultaneous learning of actions and partitions is presented and equilibrium partitions and action choices characterized. The model is able to explain deviations from subgame perfection that are sometimes observed in experiments even for vanishingly small reasoning costs. Furthermore it is shown that learning across games can stabilize mixed equilibria in 2×2 Coordination and Anti-Coordination games and destabilize strict Nash equilibria under certain conditions.

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Bibliographic Info

Paper provided by Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie) in its series Working Papers. Serie AD with number 2007-05.

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Length: 35 pages
Date of creation: Apr 2007
Date of revision:
Publication status: Published by Ivie
Handle: RePEc:ivi:wpasad:2007-05

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Keywords: Game Theory; Bounded Rationality; Reinforcement Learning; Analogies.;

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References

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Citations

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Cited by:
  1. Mohlin, Erik, 2009. "Optimal Categorization," Working Paper Series in Economics and Finance 721, Stockholm School of Economics, revised 08 Jul 2009.
  2. Mohlin, Erik, 2010. "Evolution of Theories of Mind," Working Paper Series in Economics and Finance 0728, Stockholm School of Economics, revised 12 May 2010.
  3. Gabor Lugosi & Omiros Papaspiliopoulos & Gilles Stoltz, 2009. "Online Multi-task Learning with Hard Constraints," Working Papers hal-00362643, HAL.
  4. K.J.M. De Jaegher & B. Hoyer, 2012. "Cooperation and the common enemy effect," Working Papers 12-24, Utrecht School of Economics.
  5. Grimm, Veronika & Mengel, Friederike, 2012. "An experiment on learning in a multiple games environment," Journal of Economic Theory, Elsevier, vol. 147(6), pages 2220-2259.
  6. repec:hal:wpaper:halshs-00572528 is not listed on IDEAS
  7. Friederike Mengel & Emanuela Sciubba, 2010. "Extrapolation in Games of Coordination and Dominance Solvable Games," Working Papers 2010.148, Fondazione Eni Enrico Mattei.
  8. Christoph March, 2011. "Adaptive social learning," PSE Working Papers halshs-00572528, HAL.
  9. Steiner, Jakub & Stewart, Colin, 2008. "Contagion through learning," Theoretical Economics, Econometric Society, vol. 3(4), December.
  10. Heller, Yuval & Winter, Eyal, 2013. "Rule Rationality," MPRA Paper 48746, University Library of Munich, Germany.
  11. Edward W. Piotrowski & Jan Sladkowski & Anna Szczypinska, . "Reinforcement Learning in Market Games," Departmental Working Papers 30, University of Bialtystok, Department of Theoretical Physics.
  12. Arina Nikandrova, 2013. "Repeated Play of Families of Games by Resource-Constrained Players," Games, MDPI, Open Access Journal, vol. 4(3), pages 339-346, July.

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