152 citations · 187 across the 2 of their papers we have counts for
2 papers
cs.LG2012★ 152 cited
A Bayesian Sampling Approach to Exploration in Reinforcement Learning
John Asmuth, Lihong Li, Michael L. Littman +2
We present a modular approach to reinforcement learning that uses a Bayesian representation of the uncertainty over models. The approach, BOSS (Best of Sampled Set), drives explora…
cs.AI2012★ 35 cited
Learning is planning: near Bayes-optimal reinforcement learning via Monte-Carlo tree search
John Asmuth, Michael L. Littman
Bayes-optimal behavior, while well-defined, is often difficult to achieve. Recent advances in the use of Monte-Carlo tree search (MCTS) have shown that it is possible to act near-o…