90 citations · 115 across the 14 of their papers we have counts for
3 papers · 1 filter
Reward Prediction Error as an Exploration Objective in Deep RL
Riley Simmons-Edler, Ben Eisner, Daniel Yang +4
A major challenge in reinforcement learning is exploration, when local dithering methods such as epsilon-greedy sampling are insufficient to solve a given task. Many recent methods…
Pixels to Plans: Learning Non-Prehensile Manipulation by Imitating a Planner
Tarik Tosun, Eric Mitchell, Ben Eisner +6
We present a novel method enabling robots to quickly learn to manipulate objects by leveraging a motion planner to generate "expert" training trajectories from a small amount of hu…
Q-Learning for Continuous Actions with Cross-Entropy Guided Policies
Riley Simmons-Edler, Ben Eisner, Eric Mitchell +2
Off-Policy reinforcement learning (RL) is an important class of methods for many problem domains, such as robotics, where the cost of collecting data is high and on-policy methods…