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METHODS article

Front. Blockchain
Sec. Blockchain Economics
Volume 7 - 2024 | doi: 10.3389/fbloc.2024.1448160

DeTEcT: Dynamic and Probabilistic Parameters Extension Modelling wealth distribution in token economies with time-dependent parameters

Provisionally accepted
Rem Sadykhov Rem Sadykhov *Geoff Goodell Geoff Goodell *Philip Treleaven Philip Treleaven
  • University College London, London, United Kingdom

The final, formatted version of the article will be published soon.

    This paper presents a theoretical extension of the DeTEcT framework proposed by Sadykhov et al. [1], 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.

    Keywords: Detect, tokenomics, Token Economy, Economy Simulation, Blockchain economy, mechanism design, Simulation engine, Control Theory in Economics

    Received: 12 Jun 2024; Accepted: 05 Dec 2024.

    Copyright: © 2024 Sadykhov, Goodell and Treleaven. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence:
    Rem Sadykhov, University College London, London, United Kingdom
    Geoff Goodell, University College London, London, United Kingdom

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.