Towards Optimal Policy Improvement
Practical Reinforcement Learning (RL) algorithms learn to solve Markov Decision Processes (MDPs) through iterative policy improvement in the presence of approximate evaluation. We study policy improvement from first principles, defining optimal policy improvement as producing the best policy attainable in a single upda...
Yaniv Oren, Viliam Vadocz, W. Zabka et al.
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