Closing the Learning-Planning Loop with Predictive State Representations (Extended Abstract) Byron Boots ∗ - Predictive state representation - Document - PDFSEARCH.IO - Document Search Engine

Back to Results

First Page	Meta Content
	Closing the Learning-Planning Loop with Predictive State Representations (Extended Abstract) Byron Boots ∗ Add to Reading List Document Date: 2010-03-03 14:18:55 Open Document File Size: 1,44 MB Share Result on Facebook City Toronto / / Company Processing Systems / Multiagent Systems / Google / A. R. Cassandra L. P. / / Country Canada / / / Facility Robotics Institute Carnegie Mellon University / Machine Learning Department Carnegie Mellon University / Stanford University / Sajid M. Siddiqi Geoffrey J. Gordon Machine Learning Department Carnegie Mellon University / / IndustryTerm linear dynamical systems / spectral algorithms / consistent spectral algorithm / timal solution / learning algorithm / learning algorithms / spectral algorithm / / Organization Sajid M. Siddiqi Geoffrey J. Gordon Machine Learning Department Carnegie Mellon University Pittsburgh / National Science Foundation / Machine Learning Department Carnegie Mellon University Pittsburgh / Stanford University / Canadian AI / USDA / Robotics Institute Carnegie Mellon University Pittsburgh / International Foundation for Autonomous Agents / / Person Sajid M. Siddiqi / Geoffrey J. Gordon / Byron Boots / P. Van Overschee / Sajid M. Siddiqi Geoffrey / / / Position ABSTRACT General / / SportsLeague Stanford University / / Technology statistically consistent spectral algorithm / learning algorithm / spectral algorithm / SMS / artificial intelligence / Machine Learning / EM algorithm / / URL www.ifaamas.org / http / SocialTag Stochastic control Markov models Cybernetics Predictive state representation Hidden Markov model Machine learning Markov decision process Algorithm Expectation–maximization algorithm Statistics