17 citations · 17 across the 3 of their papers we have counts for
5 papers
IL-flOw: Imitation Learning from Observation using Normalizing Flows
Wei-Di Chang, Juan Camilo Gamboa Higuera, Scott Fujimoto +2
We present an algorithm for Inverse Reinforcement Learning (IRL) from expert state observations only. Our approach decouples reward modelling from policy learning, unlike state-of-…
One-Shot Informed Robotic Visual Search in the Wild
Karim Koreitem, Florian Shkurti, Travis Manderson +3
We consider the task of underwater robot navigation for the purpose of collecting scientifically relevant video data for environmental monitoring. The majority of field robots that…
Underwater Multi-Robot Convoying using Visual Tracking by Detection
Florian Shkurti, Wei-Di Chang, Peter Henderson +7
We present a robust multi-robot convoying approach that relies on visual detection of the leading agent, thus enabling target following in unstructured 3-D environments. Our method…
OptionGAN: Learning Joint Reward-Policy Options using Generative Adversarial Inverse Reinforcement Learning
Peter Henderson, Wei-Di Chang, Pierre-Luc Bacon +3
Reinforcement learning has shown promise in learning policies that can solve complex problems. However, manually specifying a good reward function can be difficult, especially for…
Benchmark Environments for Multitask Learning in Continuous Domains
Peter Henderson, Wei-Di Chang, Florian Shkurti +3
As demand drives systems to generalize to various domains and problems, the study of multitask, transfer and lifelong learning has become an increasingly important pursuit. In disc…