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By Force of Habit: Self-Trapping in a Dynamical Utility Landscape

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  • Jos'e Moran
  • Antoine Fosset
  • Davide Luzzati
  • Jean-Philippe Bouchaud
  • Michael Benzaquen

Abstract

Historically, rational choice theory has focused on the utility maximization principle to describe how individuals make choices. In reality, there is a computational cost related to exploring the universe of available choices and it is often not clear whether we are truly maximizing an underlying utility function. In particular, memory effects and habit formation may dominate over utility maximisation. We propose a stylized model with a history-dependent utility function where the utility associated to each choice is increased when that choice has been made in the past, with a certain decaying memory kernel. We show that self-reinforcing effects can cause the agent to get stuck with a choice by sheer force of habit. We discuss the special nature of the transition between free exploration of the space of choice and self-trapping. We find in particular that the trapping time distribution is precisely a Zipf law at the transition, and that the self-trapped phase exhibits super-aging behaviour.

Suggested Citation

  • Jos'e Moran & Antoine Fosset & Davide Luzzati & Jean-Philippe Bouchaud & Michael Benzaquen, 2020. "By Force of Habit: Self-Trapping in a Dynamical Utility Landscape," Papers 2003.13660, arXiv.org.
  • Handle: RePEc:arx:papers:2003.13660
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    File URL: http://arxiv.org/pdf/2003.13660
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    Cited by:

    1. Mitsokapas, Evangelos & Harris, Rosemary J., 2022. "Decision-making with distorted memory: Escaping the trap of past experience," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 593(C).
    2. Stojkoski, Viktor & Karbevski, Marko & Utkovski, Zoran & Basnarkov, Lasko & Kocarev, Ljupco, 2021. "Evolution of cooperation in networked heterogeneous fluctuating environments," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 572(C).

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