activity
20162026
most citedAPPLE: Adaptive Planner Parameter Learning from Evaluative Feedback

34 citations · 65 across the 24 of their papers we have counts for

collaborators
Showing 2019Show all

6 papers · 1 filter

cs.AI2019★ 4 cited

A Narration-based Reward Shaping Approach using Grounded Natural Language Commands

Nicholas Waytowich, Sean L. Barton, Vernon Lawhern +1

While deep reinforcement learning techniques have led to agents that are successfully able to learn to perform a number of tasks that had been previously unlearnable, these techniq…

cs.RO2019

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…

cs.LG2019

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…

cs.LG2019★ 5 cited

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…

cs.LG2019

RIDM: Reinforced Inverse Dynamics Modeling for Learning from a Single Observed Demonstration

Brahma S. Pavse, Faraz Torabi, Josiah P. Hanna +2

Augmenting reinforcement learning with imitation learning is often hailed as a method by which to improve upon learning from scratch. However, most existing methods for integrating…

cs.MM2019

Grounding Natural Language Commands to StarCraft II Game States for Narration-Guided Reinforcement Learning

Nicholas Waytowich, Sean L. Barton, Vernon Lawhern +2

While deep reinforcement learning techniques have led to agents that are successfully able to learn to perform a number of tasks that had been previously unlearnable, these techniq…