Now showing items 1-3 of 3
Human-like Action Segmentation for Option Learning
(Georgia Institute of Technology, 2011)
Robots learning interactively with a human partner has several open questions, one of which is increasing the efficiency of learning. One approach to this problem in the Reinforcement Learning domain is to use options, ...
Object Focused Q-Learning for Autonomous Agents
(Georgia Institute of Technology, 2013)
We present Object Focused Q-learning (OF-Q), a novel reinforcement learning algorithm that can offer exponential speed-ups over classic Q-learning on domains composed of independent objects. An OF-Q agent treats the state ...
Automatic Task Decomposition and State Abstraction from Demonstration
(Georgia Institute of Technology, 2012-06)
Both Learning from Demonstration (LfD) and Reinforcement Learning (RL) are popular approaches for building decision-making agents. LfD applies supervised learning to a set of human demonstrations to infer and imitate the ...