Validating Designs and Finding Points of Failure: Testing ETH 1.x and ETH 2.0 Against AI Agents
By Vanessa Bridge, Olivier Bégassat
We’ve introduced the notion of machine learning algorithms in our network of simulator: Wittgenstein. We explore the different strategies that can be taken by participants in the network to attack the system or manipulate the protocol’s design to increase rewards. We focus specifically on reinforcement learning, and set up different agents that engage in different byzantine behaviours. We present results and guidelines to improve the design of protocols such as PoW, Casper and others.
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