Agent-Based Modeling for Studying the Spontaneous Emergence of Money

Mattia Di Russo, Zakaria Babutsidze, Célia da Costa Pereira (), Maurizio Iacopetta () and Andrea G. B. Tettamanzi ()
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Mattia Di Russo: Laboratoire I3S - SPARKS - Scalable and Pervasive softwARe and Knowledge Systems - I3S - Laboratoire d'Informatique, Signaux, et Systèmes de Sophia Antipolis - UNS - Université Nice Sophia Antipolis (1965 - 2019) - CNRS - Centre National de la Recherche Scientifique - UniCA - Université Côte d'Azur
Célia da Costa Pereira: Laboratoire I3S - SPARKS - Scalable and Pervasive softwARe and Knowledge Systems - I3S - Laboratoire d'Informatique, Signaux, et Systèmes de Sophia Antipolis - UNS - Université Nice Sophia Antipolis (1965 - 2019) - CNRS - Centre National de la Recherche Scientifique - UniCA - Université Côte d'Azur
Maurizio Iacopetta: SKEMA Business School
Andrea G. B. Tettamanzi: WIMMICS - Web-Instrumented Man-Machine Interactions, Communities and Semantics - CRISAM - Inria Sophia Antipolis - Méditerranée - Inria - Institut National de Recherche en Informatique et en Automatique - Laboratoire I3S - SPARKS - Scalable and Pervasive softwARe and Knowledge Systems - I3S - Laboratoire d'Informatique, Signaux, et Systèmes de Sophia Antipolis - UNS - Université Nice Sophia Antipolis (1965 - 2019) - CNRS - Centre National de la Recherche Scientifique - UniCA - Université Côte d'Azur

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Abstract: A central question in economics is how a society accepts money, defined as a commodity used as a medium of exchange, as an unplanned outcome of the individual interactions. This question has been approached theoretically in the literature and investigated by means of agent-based modeling. While an important aspect of the theory is the individual's speculative behavior, that is, the acceptance of money despite a potential short-term loss, previous work has been unable to reproduce it with boundedly rational agents. We investigate the reasons for the failure of previous work to have boundedly rational agents learn speculative strategies. Starting with an agent-based model proposed in the literature, where the intelligence of the agents is guided by a learning classifier system that is shown to be capable of learning trade strategies (core strategies) that involve short sequences of trades, we test several modifications of the original model and we come up with a set of assumptions that enable the spontaneous emergence of speculative strategies, which explain the emergence of money even when the agents have bounded rationality.

Keywords: Search and Money Reinforcement Learning Social Simulation; Search and Money; Reinforcement Learning; Social Simulation (search for similar items in EconPapers)
Date: 2022-11-17
New Economics Papers: this item is included in nep-cmp, nep-hme, nep-mon and nep-pay
Note: View the original document on HAL open archive server: https://inria.hal.science/hal-03913561v1
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Published in WI-IAT '22: The 21st IEEE/WIC/ACM International Conference on Web Intelligence and Agent Technologies, Nov 2022, Niagara Falls, Canada

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