  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.
