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|Using domain knowledge to decompose difficult control problems is a widely used technique in robotics. Previous work has automated the process of identifying some qualitative behaviors of a system, finding a decomposition of the system based on that behavior, and constructing a control policy based on that decomposition. We introduce a novel method for automatically finding decompositions of a task based on observing the behavior of a preexisting controller. Unlike previous work, these decompositions define reparameterizations of the state space that can permit simplified control of the system.|
|Trajectories, Control, Task Identification|
Associated Center(s) / Consortia:
Quality of Life Technology Center, National Robotics Engineering Center, and Center for the Foundations of Robotics
Associated Lab(s) / Group(s): Personal Robotics
|Stuart Anderson and Siddhartha Srinivasa, "Identifying Trajectory Classes in Dynamic Tasks," International Symposium on Approximate Dynamic Programming and Reinforcement Learning, April, 2007.|
author = "Stuart Anderson and Siddhartha Srinivasa",
title = "Identifying Trajectory Classes in Dynamic Tasks",
booktitle = "International Symposium on Approximate Dynamic Programming and Reinforcement Learning",
month = "April",
year = "2007",
|The Robotics Institute is part of the School of Computer Science, Carnegie Mellon University.|
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