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The Logistic Map: An AI Tool for Economists Investigating Complexity and Suggesting Policy Decisions

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Decision Economics. Designs, Models, and Techniques for Boundedly Rational Decisions (DCAI 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 805))

Abstract

The present contribution contains an original interpretation of the logistic map popularized by the biologist Robert May in 1976. This map is potentially a powerful AI tool based on a deterministic methodology having a double possibility to be applied in economics. The first application is to investigate the intrinsic complexity of real economic phenomena characterized by endogenous non-linear dynamics. The second application is to determine results, typical of a normative science, useful for suggesting policy decisions aimed to avoid chaos and unpredictability in the real economic system. In the first type of application, the logistic map can be used as an AI tool of forecasting (for previsions of bifurcations, cycles and chaos). In the second, the logistic map can be considered as an AI tool for policy makers in order to deduce the analytical conditions that ensure the economic system to be sufficiently far away from chaos and uncontrollability.

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Notes

  1. 1.

    The term “catastrophe” refers to a sudden change in a system’s developmental trajectory, or in a variable that characterizes it, caused by small changes in the initial conditions and/or in conditions outside the system.

  2. 2.

    The logistic map is a unimodal polynomial map of degree 2, defined for the closed and limited interval of real numbers [0,1]. It is typically used to study the onset of bifurcations, cycles, and deterministic chaos in situations characterized by simple nonlinear dynamics and by limits on the variable whose temporal evolution is to be analyzed.

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Authors and Affiliations

  1. Department of Philosophical, Pedagogical and Economic-Quantitative Sciences, University of Chieti-Pescara, Viale Pindaro 42, 65127, Pescara, Italy

    Carmen Pagliari & Nicola Mattoscio

Authors
  1. Carmen Pagliari
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  2. Nicola Mattoscio
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Corresponding author

Correspondence to Carmen Pagliari .

Editor information

Editors and Affiliations

  1. Department of Philosophical, Pedagogical and Economic-Quantitative Sciences, Section of Economics and Quantitative Methods, University of Chieti-Pescara, Pescara, Italy

    Edgardo Bucciarelli

  2. AI-ECON Research Center - Department of Economics, National Chengchi University, Taipei, Taiwan

    Shu-Heng Chen

  3. Departamento de Informática y Automática, Universidad de Salamanca, Salamanca, Spain

    Juan Manuel Corchado

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Pagliari, C., Mattoscio, N. (2019). The Logistic Map: An AI Tool for Economists Investigating Complexity and Suggesting Policy Decisions. In: Bucciarelli, E., Chen, SH., Corchado, J. (eds) Decision Economics. Designs, Models, and Techniques for Boundedly Rational Decisions. DCAI 2018. Advances in Intelligent Systems and Computing, vol 805. Springer, Cham. https://doi.org/10.1007/978-3-319-99698-1_3

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