2019
Diagnosing Bottlenecks in Deep Q-learning Algorithms
ICML 2019oral
Q-learning methods are a common class of algorithms used in reinforcement learning (RL). However, their behavior with function approximation, especially with neural networks, is poorly understood theoretically and empirically. In this work, we aim to experimentally investigate potential issues in Q-…