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International Workshop on Learning Classifier Systems

IWLCS 1999: Learning Classifier Systems pp 263–282Cite as

An Adaptive Agent Based Economic Model

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1813))

Abstract

In this paper we describe a simple model of adaptive agents of different types, represented by Learning Classifier Systems (LCS), which make investment decisions about a risk free bond and a risky asset under a well defined stock market environment. Our main aim is to explore the degree of reliability that artificially intelligent agents can have when applied to real life economic problems. We do this by evaluating whether an LCS is able to represent competent traders in a real market scenario in which daily stock prices and dividends are given to the agents exogenously, so permitting us to focus on the dynamics and evolution of the behaviour of these evolving traders without having to be concerned about how their actions affect the market.

We present results of adaptive and non-adaptive simulations over a period of ten years of real data of a specific stock and show that the artificial agents, by displaying different and rich behaviours evolved throughout the simulations, are able to discover and refine novel and successful sets of market strategies that can outperform baseline strategies such as buy-and-hold or merely keeping money in the bank at a good rate of interest, even though the agents pay commission on every trade.

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Author information

Authors and Affiliations

  1. Artificial Intelligence Applications Institute Division of Informatics, University of Edinburgh, 80 South Bridge, Edinburgh, EH1 1HN, Scotland

    Sonia Schulenburg & Peter Ross

Authors
  1. Sonia Schulenburg
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  2. Peter Ross
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Editor information

Editors and Affiliations

  1. Dipartimento di Elettronica ed Informatzione, Politecnico di Milano, Piazza Leonardo da Vinci n. 32, 20133, Milano, Italy

    Pier Luca Lanzi

  2. Institut für Psychologie III, Universität Würzburg, Röntgenring 11, 97070, Würzburg, Germany

    Wolfgang Stolzmann

  3. Prediction Dynamics, Concord, MA, 01742, USA

    Stewart W. Wilson

  4. Department of General Engineering, University of Illinois at Urbana-Champaign, USA

    Stewart W. Wilson

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© 2000 Springer-Verlag Berlin Heidelberg

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Schulenburg, S., Ross, P. (2000). An Adaptive Agent Based Economic Model. In: Lanzi, P.L., Stolzmann, W., Wilson, S.W. (eds) Learning Classifier Systems. IWLCS 1999. Lecture Notes in Computer Science(), vol 1813. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45027-0_14

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  • DOI: https://doi.org/10.1007/3-540-45027-0_14

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-67729-1

  • Online ISBN: 978-3-540-45027-6

  • eBook Packages: Springer Book Archive

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