Near Optimal On-Policy Control
نویسندگان
چکیده
We introduce two online gradient-based reinforcement learning algorithms with function approximation – one model based, and the other model free – for which we provide a regret analysis. Our regret analysis has the benefit that, unlike many other gradient based algorithm analyses for reinforcement learning with function approximation, it makes no probabilistic assumptions meaning that we need not assume a fixed behavior policy.
منابع مشابه
Near - Optimal Tunning of Linear Controllers Based on Genetic Algorithm and Swarm Intelligence: A Flight Control Example
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