209 citations · 718 across the 24 of their papers we have counts for
Showing 2018Show all
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cs.LG2018★ 39 cited
Woulda, Coulda, Shoulda: Counterfactually-Guided Policy Search
Lars Buesing, Theophane Weber, Yori Zwols +4
Learning policies on data synthesized by models can in principle quench the thirst of reinforcement learning algorithms for large amounts of real experience, which is often costly…
cs.LG2018★ 60 cited
Learning and Querying Fast Generative Models for Reinforcement Learning
Lars Buesing, Theophane Weber, Sebastien Racaniere +8
A key challenge in model-based reinforcement learning (RL) is to synthesize computationally efficient and accurate environment models. We show that carefully designed generative mo…