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Blockchain State Machine Representation

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  • Shorish, Jamsheed

    (Shorish Research)

Abstract

We present a formalization of blockchain as a state machine, focusing upon permissionless blockchains due to general audience awareness of its most popular implementation, Bitcoin (permissioned blockchains are treated similarly without loss of generality). After presenting a typical Bitcoin transaction workflow, a general blockchain state representation is derived. It is demonstrated that the proper mathematical object defining the state of a blockchain is a topological fiber bundle, because it is not possible to globally `parametrize' blocks (or ledgers of blocks) by time due to their dependence upon cryptographic hash functions. In addition, we specify a general transition function between blockchain states that is agnostic to the consensus mechanism used to write blocks into the ledger, and which is probabilistic in nature, so that blockchain may be regarded as a probabilistic state machine. We then interpret agents (both human and code-based, such as `chaincode', `smart contracts', or other artificial intelligence) as automata interacting with blockchain technology, drawing upon the theory of non-cooperative repeated interaction games. Finally, blockchain as a hierarchy of state machines is defined, and future research directions are presented using this hierarchy as a point of departure for modeling blockchain dynamics.

Suggested Citation

  • Shorish, Jamsheed, 2018. "Blockchain State Machine Representation," SocArXiv eusxg, Center for Open Science.
    • Handle: RePEc:osf:socarx:eusxg
    DOI: 10.31219/osf.io/eusxg
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    References listed on IDEAS

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    6. Rainer Böhme & Nicolas Christin & Benjamin Edelman & Tyler Moore, 2015. "Bitcoin: Economics, Technology, and Governance," Journal of Economic Perspectives, American Economic Association, vol. 29(2), pages 213-238, Spring.
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    Cited by:

    1. Federico Fioravanti & Fernando Tohmé, 2020. "Asking Infinite Voters ‘Who is a J?’: Group Identification Problems in ℕ$\mathbb {N}$," Journal of Classification, Springer;The Classification Society, vol. 37(1), pages 58-65, April.

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