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Feedback-based tree search for reinforcement learning
Inspired by recent successes of Monte-Carlo tree search (MCTS) in a number of artificial
intelligence (AI) application domains, we propose a reinforcement learning (RL) technique …
intelligence (AI) application domains, we propose a reinforcement learning (RL) technique …
An approximately optimal relative value learning algorithm for averaged MDPs with continuous states and actions
It has long been a challenging problem to design algorithms for Markov decision processes
(MDPs) with continuous states and actions that are provably approximately optimal and can …
(MDPs) with continuous states and actions that are provably approximately optimal and can …
Empirical algorithms for general stochastic systems with continuous states and actions
In this paper, we present Randomized Empirical Value Learning (RAEVL) algorithm for
MDPs with continuous state and action spaces. This algorithm combines the ideas of …
MDPs with continuous state and action spaces. This algorithm combines the ideas of …