Isaac S. Chan

Adaptive Tree Backup Algorithms for Temporal-Difference Reinforcement Learning

2022 · arXiv (Cornell University)

Q($σ$) is a recently proposed temporal-difference learning method that interpolates between learning from expected backups and sampled backups. It has been shown that intermediate values for the interpolation parameter $σ\in [0,1]$ perform better in practice, …