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      Agent-Based Simulations of Blockchain protocols illustrated via Kadena's Chainweb

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          Abstract

          While many distributed consensus protocols provide robust liveness and consistency guarantees under the presence of malicious actors, quantitative estimates of how economic incentives affect security are few and far between. In this paper, we describe a system for simulating how adversarial agents, both economically rational and Byzantine, interact with a blockchain protocol. This system provides statistical estimates for the economic difficulty of an attack and how the presence of certain actors influences protocol-level statistics, such as the expected time to regain liveness. This simulation system is influenced by the design of algorithmic trading and reinforcement learning systems that use explicit modeling of an agent's reward mechanism to evaluate and optimize a fully autonomous agent. We implement and apply this simulation framework to Kadena's Chainweb, a parallelized Proof-of-Work system, that contains complexity in how miner incentive compliance affects security and censorship resistance. We provide the first formal description of Chainweb that is in the literature and use this formal description to motivate our simulation design. Our simulation results include a phase transition in block height growth rate as a function of shard connectivity and empirical evidence that censorship in Chainweb is too costly for rational miners to engage in. We conclude with an outlook on how simulation can guide and optimize protocol development in a variety of contexts, including Proof-of-Stake parameter optimization and peer-to-peer networking design.

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          Randomized gossip algorithms

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            The economy needs agent-based modelling.

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              Kademlia: A Peer-to-Peer Information System Based on the XOR Metric

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                Author and article information

                Journal
                29 April 2019
                Article
                1904.12924
                8a79583e-9767-43a8-a45b-5a97e1d7454d

                http://arxiv.org/licenses/nonexclusive-distrib/1.0/

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                Custom metadata
                10 pages, 7 figures, accepted to the IEEE S&B 2019 conference
                cs.CR cs.DC cs.MA

                Security & Cryptology,Artificial intelligence,Networking & Internet architecture

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