52 citations · 61 across the 2 of their papers we have counts for
3 papers
Fast Adaptation via Policy-Dynamics Value Functions
Roberta Raileanu, Max Goldstein, Arthur Szlam +1
Standard RL algorithms assume fixed environment dynamics and require a significant amount of interaction to adapt to new environments. We introduce Policy-Dynamics Value Functions…
Automatic Data Augmentation for Generalization in Deep Reinforcement Learning
Roberta Raileanu, Max Goldstein, Denis Yarats +2
Deep reinforcement learning (RL) agents often fail to generalize to unseen scenarios, even when they are trained on many instances of semantically similar environments. Data augmen…
Learning Generalized Reactive Policies using Deep Neural Networks
Edward Groshev, Maxwell Goldstein, Aviv Tamar +2
We present a new approach to learning for planning, where knowledge acquired while solving a given set of planning problems is used to plan faster in related, but new problem insta…