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The Neuroeconomics of Learning and Information Processing; Applying Markov Decision Process

  • Chatterjee, Sidharta

This paper deals with cognitive theories behind agent-based modeling of learning and information processing methodologies. Herein, I undertake a descriptive analysis of how human agents learn to select action and maximize their value function under reinforcement learning model. In doing so, I have considered the spatio-temporal environment under bounded rationality using Markov Decision process modeling to generalize patterns of agent behavior by analyzing the determinants of value functions, and of factors that modify policy- action-induced cognitive abilities. Since detecting patterns are central to the human cognitive skills, this paper aspires at uncovering the entanglements of complex contextual pattern identification by linking contexts with optimal decisions that agents undertake under hypercompetitive market pressure through learning which have however, implicative applications in a wide array of social and macroeconomic domains.

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File URL: http://mpra.ub.uni-muenchen.de/28883/1/MPRA_paper_28883.pdf
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File URL: http://mpra.ub.uni-muenchen.de/28983/1/MPRA_paper_28983.pdf
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File URL: http://mpra.ub.uni-muenchen.de/28993/3/MPRA_paper_28993.pdf
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Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 28883.

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Date of creation: 14 Feb 2011
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Handle: RePEc:pra:mprapa:28883
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  1. Herbert Simon, 2000. "Bounded rationality in social science: Today and tomorrow," Mind and Society: Cognitive Studies in Economics and Social Sciences, Fondazione Rosselli, vol. 1(1), pages 25-39, March.
  2. Luigi Marengo & Giovanni Dosi & Paolo Legrenzi & Corrado Pasquali, 1999. "The structure of problem-solving knowledge and the structure of organisations," LEM Papers Series 1999/09, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
  3. Daniel Houser & Michael Keane & Kevin McCabe, 2004. "Behavior in a Dynamic Decision Problem: An Analysis of Experimental Evidence Using a Bayesian Type Classification Algorithm," Econometrica, Econometric Society, vol. 72(3), pages 781-822, 05.
  4. P. Mongin & C. d'Aspremont, 1996. "Utility theory and ethics," THEMA Working Papers 96-32, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
  5. Ralph-C. Bayer & Ludovic Renou, 2011. "Cognitive abilities and behavior in strategic-form games.," Discussion Papers in Economics 11/16, Department of Economics, University of Leicester.
  6. Anat Bracha & Donald J. Brown, 2010. "Affective Decision-Making: A Theory of Optimism-Bias," Cowles Foundation Discussion Papers 1759, Cowles Foundation for Research in Economics, Yale University.
  7. Simon, Herbert A., 1978. "Rational Decision-Making in Business Organizations," Nobel Prize in Economics documents 1978-1, Nobel Prize Committee.
  8. Giovanni Dosi & Marco Faillo & Luigi Marengo & Daniele Moschella, 2011. "Toward Formal Representations of Search Processes and Routines in Organizational Problem Solving. An Assessment of the State of the Art," LEM Papers Series 2011/04, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
  9. Egidi Massimo & Rizzello Salvatore, 2003. "Cognitive economics: Foundations and historical evolution," CESMEP Working Papers 200304, University of Turin.
  10. Tesfatsion, Leigh & Judd, Kenneth L., 2006. "Handbook of Computational Economics, Vol. 2: Agent-Based Computational Economics," Staff General Research Papers 10368, Iowa State University, Department of Economics.
  11. Novarese, Marco & Lanteri, Alessandro, 2007. "Individual learning: theory formation, and feedback in a complex task," MPRA Paper 3049, University Library of Munich, Germany.
  12. Anat Bracha & Donald J. Brown, 2010. "Affective decision making: a theory of optimism bias," Working Papers 10-16, Federal Reserve Bank of Boston.
  13. Anat Bracha & Donald Brown, 2010. "Affective Decision-Making: A Theory of Optimism-Bias," Levine's Working Paper Archive 661465000000000123, David K. Levine.
  14. Kahneman, Daniel & Tversky, Amos, 1979. "Prospect Theory: An Analysis of Decision under Risk," Econometrica, Econometric Society, vol. 47(2), pages 263-91, March.
  15. Salvatore Rizzello, 2004. "Knowledge as a Path-Dependence Process," Journal of Bioeconomics, Springer, vol. 6(3), pages 255-274, 09.
  16. Herbert A. Simon, 1999. "The many shapes of knowledge," Revue d'Économie Industrielle, Programme National Persée, vol. 88(1), pages 23-39.
  17. Paul David, 1997. "Path Dependence and the Quest for Historical Economics: One More chorus of Ballad of QWERTY," Economics Series Working Papers 1997-W20, University of Oxford, Department of Economics.
  18. Leigh Tesfatsion, 2002. "Agent-Based Computational Economics," Computational Economics 0203001, EconWPA, revised 15 Aug 2002.
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