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Our Approach to Formal Verification of Token Economy Models

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Information and Communication Technologies in Education, Research, and Industrial Applications (ICTERI 2019)

Abstract

The tokenomic modeling is one of the most efficient approaches for understanding and prediction of its subject’s behavior. There are many tools for simulation modeling of behavior in different domains but there is lack of examples in literature on the usage for tokenomic modeling. The paper considers the formal methods approach for tokenomic modeling. Thus, this article provides a brief description of the technology and the methods and tools developed by the authors for token economy modeling and for the analysis and study of its properties. The article also describes the formalization of the tokenomics model on the example of the SKILLONOMY project and presents the specific and symbolic SKILLONOMY models and its simulation results. The formalization and properties analysis is considered with usage of insertion modeling platform.

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Acknowledgements

We would like to thank the company garuda.ai [17] for the opportunity to work with the platform for modeling, formal verification and testing of Blockchain/DLT systems behavior and cybersecurity research for our research and experiments in the modeling area. We are also grateful to the Glushkov Institute of Cybernetics of NAS of Ukraine for the theoretical and practical results in the field of verification that were used as a basis for our studies of formalization and algebraic modeling in the tokenomics projects area and to the Kherson State University for the active supporting of Insertion Modeling System.

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Correspondence to Maksym Poltoratskyi .

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Letychevskyi, O., Peschanenko, V., Poltoratskyi, M., Tarasich, Y. (2020). Our Approach to Formal Verification of Token Economy Models. In: Ermolayev, V., Mallet, F., Yakovyna, V., Mayr, H., Spivakovsky, A. (eds) Information and Communication Technologies in Education, Research, and Industrial Applications. ICTERI 2019. Communications in Computer and Information Science, vol 1175. Springer, Cham. https://doi.org/10.1007/978-3-030-39459-2_16

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  • DOI: https://doi.org/10.1007/978-3-030-39459-2_16

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-39458-5

  • Online ISBN: 978-3-030-39459-2

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