101 citations · 198 across the 12 of their papers we have counts for
4 papers · 1 filter
Is Conditional Generative Modeling all you need for Decision-Making?
Anurag Ajay, Yilun Du, Abhi Gupta +3
Recent improvements in conditional generative modeling have made it possible to generate high-quality images from language descriptions alone. We investigate whether these methods…
Distributionally Adaptive Meta Reinforcement Learning
Anurag Ajay, Abhishek Gupta, Dibya Ghosh +2
Meta-reinforcement learning algorithms provide a data-driven way to acquire policies that quickly adapt to many tasks with varying rewards or dynamics functions. However, learned m…
Offline RL Policies Should be Trained to be Adaptive
Dibya Ghosh, Anurag Ajay, Pulkit Agrawal +1
Offline RL algorithms must account for the fact that the dataset they are provided may leave many facets of the environment unknown. The most common way to approach this challenge…
Overcoming the Spectral Bias of Neural Value Approximation
Ge Yang, Anurag Ajay, Pulkit Agrawal
Value approximation using deep neural networks is at the heart of off-policy deep reinforcement learning, and is often the primary module that provides learning signals to the rest…