Now showing items 1-3 of 3
Eﬃcient and principled robot learning: Theory and algorithms
(Georgia Institute of Technology, 2020-01-07)
Roboticists have long envisioned fully-automated robots that can operate reliably in unstructured environments. This is an exciting but extremely difficult problem; in order to succeed, robots must reason about sequential ...
Manipulating state space distributions for sample-efficient imitation-learning
(Georgia Institute of Technology, 2020-03-16)
Imitation learning has emerged as one of the most effective approaches to train agents to act intelligently in unstructured and unknown domains. On its own or in combination with reinforcement learning, it enables agents ...
Emulation and imitation via perceptual goal specifications
(Georgia Institute of Technology, 2019-04-02)
This dissertation aims to demonstrate how perceptual goal specifications may be used as alternative representations for specifying domain-specific reward functions for reinforcement learning. The works outlined in this ...