14 citations · 19 across the 3 of their papers we have counts for
9 papers
Recent Advances in Leveraging Human Guidance for Sequential Decision-Making Tasks
Ruohan Zhang, Faraz Torabi, Garrett Warnell +1
A longstanding goal of artificial intelligence is to create artificial agents capable of learning to perform tasks that require sequential decision making. Importantly, while it is…
DEALIO: Data-Efficient Adversarial Learning for Imitation from Observation
Faraz Torabi, Garrett Warnell, Peter Stone
In imitation learning from observation IfO, a learning agent seeks to imitate a demonstrating agent using only observations of the demonstrated behavior without access to the contr…
Leveraging Human Guidance for Deep Reinforcement Learning Tasks
Ruohan Zhang, Faraz Torabi, Lin Guan +2
Reinforcement learning agents can learn to solve sequential decision tasks by interacting with the environment. Human knowledge of how to solve these tasks can be incorporated usin…
Recent Advances in Imitation Learning from Observation
Faraz Torabi, Garrett Warnell, Peter Stone
Imitation learning is the process by which one agent tries to learn how to perform a certain task using information generated by another, often more-expert agent performing that sa…
Imitation Learning from Video by Leveraging Proprioception
Faraz Torabi, Garrett Warnell, Peter Stone
Classically, imitation learning algorithms have been developed for idealized situations, e.g., the demonstrations are often required to be collected in the exact same environment a…
Sample-efficient Adversarial Imitation Learning from Observation
Faraz Torabi, Sean Geiger, Garrett Warnell +1
Imitation from observation is the framework of learning tasks by observing demonstrated state-only trajectories. Recently, adversarial approaches have achieved significant performa…