Engineering Token Economy with System Modeling

• DOI: 10.48550/arxiv.1907.00899
• Publication Date: 2019-01-01
• Authors: Zhang, Zixuan
• Keywords: FOS: Computer and information sciences; 0209 industrial biotechnology; Computer Science - Multiagent Systems; 02 engineering and technology; Multiagent Systems (cs.MA)

Cryptocurrencies and blockchain networks have attracted tremendous attention from their volatile price movements and the promise of decentralization. However, most projects run on business narratives with no way to test and verify their assumptions and promises about the future. The complex nature of system dynamics within networked economies has rendered it difficult to reason about the growth and evolution of these networks. This paper drew concepts from differential games, classical control engineering, and stochastic dynamical system to come up with a framework and example to model, simulate, and engineer networked token economies. A model on a generalized token economy is proposed where miners provide service to a platform in exchange for a cryptocurrency and users consume service from the platform. Simulations of this model allow us to observe outcomes of complex dynamics and reason about the evolution of the system. Speculative price movements and engineered block rewards were then experimented to observe their impact on system dynamics and network-level goals. The model presented is necessarily limited so we conclude by exploring those limitations and outlining future research directions.