1 citations · 1 across the 1 of their papers we have counts for
2 papers
cs.LG2022★ 1 cited
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…
cs.LG2020
Counterfactual Data Augmentation using Locally Factored Dynamics
Silviu Pitis, Elliot Creager, Animesh Garg
Many dynamic processes, including common scenarios in robotic control and reinforcement learning (RL), involve a set of interacting subprocesses. Though the subprocesses are not in…