WeRLman

Abstract

Blockchain technology is responsible for the emergence of cryptocurrencies, such as Bitcoin and Ethereum. The security of a blockchain protocol relies on the incentives of its participants. Selfish mining is a form of deviation from the protocol where a participant can gain more than her fair share. Previous analyses of selfish mining make easing, non-realistic assumptions. We introduce a more realistic model with varying block rewards in the form of transaction fees. However, this comes at the cost of an intractable state space. To solve the complex model, we introduce WeRLman, a novel method based on deep Reinforcement Learning (deep RL). Using WeRLman, we show reward variability can significantly hurt blockchain security.