Two papers on Reinforcement Learning accepted at NeurIPS 2020!

Our two papers on scalable control and multi-agent reinforcement learning have been accepted as posters to the 34th edition of Neural Information Processing Systems (NeurIPS) 2020 as part of the Deep Reinforcement Learning Workshop. These papers are part of an ongoing project on high-frequency market trading. Please see our publications for the two papers:

1. Maximum Mutation Reinforcement Learning for Scalable Control

2. Energy-based Surprise Minimization for Multi-Agent Value Factorization