228 citations · 642 across the 22 of their papers we have counts for
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stat.ML2017★ 160 cited
Deep Exploration via Randomized Value Functions
Ian Osband, Benjamin Van Roy, Daniel Russo +1
We study the use of randomized value functions to guide deep exploration in reinforcement learning. This offers an elegant means for synthesizing statistically and computationally…
stat.ML2013★ 228 cited
(More) Efficient Reinforcement Learning via Posterior Sampling
Ian Osband, Daniel Russo, Benjamin Van Roy
Most provably-efficient learning algorithms introduce optimism about poorly-understood states and actions to encourage exploration. We study an alternative approach for efficient e…