451 citations · 1.7k across the 73 of their papers we have counts for
Showing 2014 · stat.MLShow all
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stat.ML2014★ 43 cited
Model-based Reinforcement Learning and the Eluder Dimension
Ian Osband, Benjamin Van Roy
We consider the problem of learning to optimize an unknown Markov decision process (MDP). We show that, if the MDP can be parameterized within some known function class, we can obt…
stat.ML2014★ 45 cited
Near-optimal Reinforcement Learning in Factored MDPs
Ian Osband, Benjamin Van Roy
Any reinforcement learning algorithm that applies to all Markov decision processes (MDPs) will suffer regret on some MDP, where is the elapsed time and and…
stat.ML2014★ 80 cited
Generalization and Exploration via Randomized Value Functions
Ian Osband, Benjamin Van Roy, Zheng Wen
We propose randomized least-squares value iteration (RLSVI) -- a new reinforcement learning algorithm designed to explore and generalize efficiently via linearly parameterized valu…