1 citations · 2 across the 3 of their papers we have counts for
3 papers
Policy Gradients Incorporating the Future
David Venuto, Elaine Lau, Doina Precup +1
Reasoning about the future -- understanding how decisions in the present time affect outcomes in the future -- is one of the central challenges for reinforcement learning (RL), esp…
oIRL: Robust Adversarial Inverse Reinforcement Learning with Temporally Extended Actions
David Venuto, Jhelum Chakravorty, Leonard Boussioux +3
Explicit engineering of reward functions for given environments has been a major hindrance to reinforcement learning methods. While Inverse Reinforcement Learning (IRL) is a soluti…
Avoidance Learning Using Observational Reinforcement Learning
David Venuto, Leonard Boussioux, Junhao Wang +4
Imitation learning seeks to learn an expert policy from sampled demonstrations. However, in the real world, it is often difficult to find a perfect expert and avoiding dangerous be…