Target Network and Truncation Overcome The Deadly Triad in $Q$-Learning

no code implementations • 5 Mar 2022 • Zaiwei Chen, John Paul Clarke, Siva Theja Maguluri

$Q$-learning with function approximation is one of the most empirically successful while theoretically mysterious reinforcement learning (RL) algorithms, and was identified in Sutton (1999) as one of the most important theoretical open problems in the RL community.

Q-Learning reinforcement-learning +1