71 citations · 110 across the 28 of their papers we have counts for
3 papers · 1 filter
Learning and Retrieval from Prior Data for Skill-based Imitation Learning
Soroush Nasiriany, Tian Gao, Ajay Mandlekar +1
Imitation learning offers a promising path for robots to learn general-purpose behaviors, but traditionally has exhibited limited scalability due to high data supervision requireme…
MoCoDA: Model-based Counterfactual Data Augmentation
Silviu Pitis, Elliot Creager, Ajay Mandlekar +1
The number of states in a dynamic process is exponential in the number of objects, making reinforcement learning (RL) difficult in complex, multi-object domains. For agents to scal…
AC-Teach: A Bayesian Actor-Critic Method for Policy Learning with an Ensemble of Suboptimal Teachers
Andrey Kurenkov, Ajay Mandlekar, Roberto Martin-Martin +2
The exploration mechanism used by a Deep Reinforcement Learning (RL) agent plays a key role in determining its sample efficiency. Thus, improving over random exploration is crucial…