Keywords: reinforcement learning, Q-learning, monotone, numerical methods
Abstract: Stability issues with reinforcement learning methods persist.
To better understand some of these stability and convergence issues involving deep reinforcement learning methods, we examine a simple linear quadratic example.
We interpret the convergence criterion of exact Q-learning in the sense of a monotone scheme and discuss consequences of function approximation on monotonicity properties.
Submission Number: 101
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