2022
The Pitfalls of Regularization in Off-Policy TD Learning
NeurIPS 2022accept
Temporal Difference (TD) learning is ubiquitous in reinforcement learning, where it is often combined with off-policy sampling and function approximation. Unfortunately learning with this combination (known as the deadly triad), exhibits instability and unbounded error. To account for this, modern…