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Learning in hidden Markov models with bounded memory

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  • Monte, Daniel
  • Said, Maher

Abstract

This paper explores the role of memory in decision making in dynamic environments. We examine the inference problem faced by an agent with bounded memory who receives a sequence of signals from a hidden Markov model. We show that the optimal symmetric memory rule may be deterministic. This result contrasts sharply with Hellman and Cover (1970) and Wilson (2004) and solves, for the context of a hidden Markov model, an open question posed by Kalai and Solan (2003).

Suggested Citation

  • Monte, Daniel & Said, Maher, 2010. "Learning in hidden Markov models with bounded memory," MPRA Paper 23854, University Library of Munich, Germany, revised 23 Jun 2010.
  • Handle: RePEc:pra:mprapa:23854
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    References listed on IDEAS

    as
    1. Monte, Daniel, 2014. "Learning with bounded memory in games," Games and Economic Behavior, Elsevier, vol. 87(C), pages 204-223.
    2. Kalai, Ehud & Solan, Eilon, 2003. "Randomization and simplification in dynamic decision-making," Journal of Economic Theory, Elsevier, vol. 111(2), pages 251-264, August.
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    6. Aumann, Robert J. & Sorin, Sylvain, 1989. "Cooperation and bounded recall," Games and Economic Behavior, Elsevier, vol. 1(1), pages 5-39, March.
    7. Kalai, Ehud & Stanford, William, 1988. "Finite Rationality and Interpersonal Complexity in Repeated Games," Econometrica, Econometric Society, vol. 56(2), pages 397-410, March.
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    9. Olivier Compte & Andrew Postlewaite, 2007. "Effecting Cooperation," PIER Working Paper Archive 09-019, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 29 May 2009.
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    11. Luca Anderlini & Roger Lagunoff, 2005. "Communication in dynastic repeated games: ‘Whitewashes’ and ‘coverups’," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 26(2), pages 265-299, August.
    12. Luca Anderlini & Dino Gerardi & Roger Lagunoff, 2008. "A “Super” Folk Theorem for dynastic repeated games," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 37(3), pages 357-394, December.
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    Cited by:

    1. Mueller-Frank, Manuel, 2015. "Reaching Consensus in Social Networks," IESE Research Papers D/1116, IESE Business School.
    2. Carlos Alós-Ferrer & Nick Netzer, 2015. "Robust stochastic stability," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 58(1), pages 31-57, January.

    More about this item

    Keywords

    Bounded Memory; Hidden Markov Model; Randomization.;

    JEL classification:

    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games
    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games

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