no code implementations • 15 Nov 2023 • Wei-Di Chang, Francois Hogan, David Meger, Gregory Dudek
In this paper we leverage self-supervised vision transformer models and their emergent semantic abilities to improve the generalization abilities of imitation learning policies.
no code implementations • 2 Oct 2023 • Wei-Di Chang, Scott Fujimoto, David Meger, Gregory Dudek
Imitation Learning from Observation (ILfO) is a setting in which a learner tries to imitate the behavior of an expert, using only observational data and without the direct guidance of demonstrated actions.
2 code implementations • NeurIPS 2023 • Scott Fujimoto, Wei-Di Chang, Edward J. Smith, Shixiang Shane Gu, Doina Precup, David Meger
In the field of reinforcement learning (RL), representation learning is a proven tool for complex image-based tasks, but is often overlooked for environments with low-level states, such as physical control problems.
no code implementations • 3 Feb 2023 • Igor Kozlov, Dmitriy Rivkin, Wei-Di Chang, Di wu, Xue Liu, Gregory Dudek
Such networks undergo frequent and often heterogeneous changes caused by network operators, who are seeking to tune their system parameters for optimal performance.
no code implementations • 19 May 2022 • Wei-Di Chang, Juan Camilo Gamboa Higuera, Scott Fujimoto, David Meger, Gregory Dudek
We present an algorithm for Inverse Reinforcement Learning (IRL) from expert state observations only.
1 code implementation • 22 Mar 2020 • Karim Koreitem, Florian Shkurti, Travis Manderson, Wei-Di Chang, Juan Camilo Gamboa Higuera, Gregory Dudek
In this paper we propose a method that enables informed visual navigation via a learned visual similarity operator that guides the robot's visual search towards parts of the scene that look like an exemplar image, which is given by the user as a high-level specification for data collection.
1 code implementation • 25 Sep 2017 • Florian Shkurti, Wei-Di Chang, Peter Henderson, Md Jahidul Islam, Juan Camilo Gamboa Higuera, Jimmy Li, Travis Manderson, Anqi Xu, Gregory Dudek, Junaed Sattar
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.
1 code implementation • 20 Sep 2017 • Peter Henderson, Wei-Di Chang, Pierre-Luc Bacon, David Meger, Joelle Pineau, Doina Precup
Inverse reinforcement learning offers a useful paradigm to learn the underlying reward function directly from expert demonstrations.
1 code implementation • 14 Aug 2017 • Peter Henderson, Wei-Di Chang, Florian Shkurti, Johanna Hansen, David Meger, Gregory Dudek
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.