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DeTEcT: Dynamic and Probabilistic Parameters Extension

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  • Rem Sadykhov
  • Geoffrey Goodell
  • Philip Treleaven

Abstract

This paper presents a theoretical extension of the DeTEcT framework proposed by Sadykhov et al., DeTEcT, where a formal analysis framework was introduced for modelling wealth distribution in token economies. DeTEcT is a framework for analysing economic activity, simulating macroeconomic scenarios, and algorithmically setting policies in token economies. This paper proposes four ways of parametrizing the framework, where dynamic vs static parametrization is considered along with the probabilistic vs non-probabilistic. Using these parametrization techniques, we demonstrate that by adding restrictions to the framework it is possible to derive the existing wealth distribution models from DeTEcT. In addition to exploring parametrization techniques, this paper studies how money supply in DeTEcT framework can be transformed to become dynamic, and how this change will affect the dynamics of wealth distribution. The motivation for studying dynamic money supply is that it enables DeTEcT to be applied to modelling token economies without maximum supply (i.e., Ethereum), and it adds constraints to the framework in the form of symmetries.

Suggested Citation

  • Rem Sadykhov & Geoffrey Goodell & Philip Treleaven, 2024. "DeTEcT: Dynamic and Probabilistic Parameters Extension," Papers 2405.16688, arXiv.org.
    • Handle: RePEc:arx:papers:2405.16688
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    1. M. Patriarca & A. Chakraborti & E. Heinsalu & G. Germano, 2007. "Relaxation in statistical many-agent economy models," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 57(2), pages 219-224, May.
    2. Anirban Chakraborti & Bikas K. Chakrabarti, 2000. "Statistical mechanics of money: How saving propensity affects its distribution," Papers cond-mat/0004256, arXiv.org, revised Jun 2000.
    3. Marco Patriarca & Anirban Chakraborti & Kimmo Kaski & Guido Germano, 2005. "Kinetic theory models for the distribution of wealth: power law from overlap of exponentials," Papers physics/0504153, arXiv.org, revised May 2005.
    4. Rem Sadykhov & Geoffrey Goodell & Denis de Montigny & Martin Schoernig & Philip Treleaven, 2023. "Decentralized Token Economy Theory (DeTEcT)," Papers 2309.12330, arXiv.org, revised Jan 2024.
    5. A. Chakraborti & B.K. Chakrabarti, 2000. "Statistical mechanics of money: how saving propensity affects its distribution," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 17(1), pages 167-170, September.
    6. Anirban Chakraborti, 2002. "Distributions Of Money In Model Markets Of Economy," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 13(10), pages 1315-1321.
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