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Minority Game and the Wealth Distribution in the Artificial Market

  • Conference paper
Knowledge-Based Intelligent Information and Engineering Systems (KES 2005)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3681))

Abstract

We focus on the wealth-distribution problem in an artificial market in the context of multi-agent modeling in which trading activity is represented by the minority game. This model is widely investigated in the community of computational intelligence and econo-physics, due to its rich contents including the emergence of self-organization among agents, natural incorporation of limited rationality of agents, and good affinity to evolutional computation. However, the major defect of this kind of models is the difficulty in quantitatively explaining the constitution of the society in comparison to the real society. In particular, the wealth distribution among agents does not follow the scale-invariant distribution known as Pareto’s law. We consider two new elements to be added to the standard minority game in order to make the resulting wealth distribution of the society to fit the real-world value.

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Author information

Authors and Affiliations

  1. Department of Information and Knowledge Engineering, Tottori University, Tottori, 680-8552, Japan

    Mieko Tanaka-Yamawaki

Authors
  1. Mieko Tanaka-Yamawaki
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Editor information

Editors and Affiliations

  1. School of Business, La Trobe University, 3086, Melbourne, Victoria, Australia

    Rajiv Khosla

  2. Centre for SMART systems Engineering Research Centre, University of Brighton, Moulsecoomb, BN2 4GJ, Brighton, UK

    Robert J. Howlett

  3. School of Electrical and Information Engineering, Knowledge Based Intelligent Engineering Systems Centre, University of South Australia, 5095, Mawson Lakes, SA, Australia

    Lakhmi C. Jain

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© 2005 Springer-Verlag Berlin Heidelberg

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Tanaka-Yamawaki, M. (2005). Minority Game and the Wealth Distribution in the Artificial Market. In: Khosla, R., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2005. Lecture Notes in Computer Science(), vol 3681. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11552413_3

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  • DOI: https://doi.org/10.1007/11552413_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28894-7

  • Online ISBN: 978-3-540-31983-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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