A Unified Approach for Multi-step Temporal-Difference Learning with Eligibility Traces in Reinforcement Learning

Long Yang, Minhao Shi, Qian Zheng +2

Recently, a new multi-step temporal learning algorithm, called $Q(\sigma )$, unifies $n$-step Tree-Backup (when $\sigma =0$) and $n$-step Sarsa (when $\sigma =1$) by introducing a sampling parameter…