On the Reduction of Variance and Overestimation of Deep Q-Learning

no code implementations • 14 Oct 2019 • Mohammed Sabry, Amr M. A. Khalifa

The breakthrough of deep Q-Learning on different types of environments revolutionized the algorithmic design of Reinforcement Learning to introduce more stable and robust algorithms, to that end many extensions to deep Q-Learning algorithm have been proposed to reduce the variance of the target values and the overestimation phenomena.

Q-Learning reinforcement-learning +1