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A Markov Decision Process with Awareness and Present Bias in Decision-Making

Author

Listed:
  • Federico Bizzarri

    (Department of Information Engineering and Mathematics, University of Siena, Via Roma, 56, 53100 Siena, Italy)

  • Chiara Mocenni

    (Department of Information Engineering and Mathematics, University of Siena, Via Roma, 56, 53100 Siena, Italy)

  • Silvia Tiezzi

    (Department of Economics and Statistics, University of Siena, Piazza San Francesco, 7/8, 53100 Siena, Italy)

Abstract

We propose a Markov Decision Process Model that blends ideas from Psychological research and Economics to study decision-making in individuals with self-control problems. We have borrowed a dual-process of decision-making with self-awareness from Psychological research, and we introduce present bias in inter-temporal preferences, a phenomenon widely explored in Economics. We allow for both an exogenous and endogenous, state-dependent, present bias in inter-temporal decision-making and explore, by means of numerical simulations, the consequences on well-being emerging from the solution of the model. We show that, over time, self-awareness may mitigate present bias and suboptimal choice behaviour.

Suggested Citation

  • Federico Bizzarri & Chiara Mocenni & Silvia Tiezzi, 2023. "A Markov Decision Process with Awareness and Present Bias in Decision-Making," Mathematics, MDPI, vol. 11(11), pages 1-12, June.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:11:p:2588-:d:1164363
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    References listed on IDEAS

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    Cited by:

    1. Chuanhao Fan & Jiaxin Wang & Yan Zhu & Hengjie Zhang, 2024. "A Consensus-Based 360 Degree Feedback Evaluation Method with Linguistic Distribution Assessments," Mathematics, MDPI, vol. 12(12), pages 1-20, June.

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