2019
Woulda, Coulda, Shoulda: Counterfactually-Guided Policy Search
ICLR 2019poster
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 to acquire. However, simulating plausible experience de novo is a hard problem for many complex environments, often resu…