257 citations · 1k across the 96 of their papers we have counts for
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Natural Environment Benchmarks for Reinforcement Learning
Amy Zhang, Yuxin Wu, Joelle Pineau
While current benchmark reinforcement learning (RL) tasks have been useful to drive progress in the field, they are in many ways poor substitutes for learning with real-world data.…
A Dissection of Overfitting and Generalization in Continuous Reinforcement Learning
Amy Zhang, Nicolas Ballas, Joelle Pineau
The risks and perils of overfitting in machine learning are well known. However most of the treatment of this, including diagnostic tools and remedies, was developed for the superv…
Decoupling Dynamics and Reward for Transfer Learning
Amy Zhang, Harsh Satija, Joelle Pineau
Current reinforcement learning (RL) methods can successfully learn single tasks but often generalize poorly to modest perturbations in task domain or training procedure. In this wo…
Composable Planning with Attributes
Amy Zhang, Adam Lerer, Sainbayar Sukhbaatar +2
The tasks that an agent will need to solve often are not known during training. However, if the agent knows which properties of the environment are important then, after learning h…