Batch-iFDD for representation expansion in large MDPs

Batch-iFDD for representation expansion in large MDPs

Matching pursuit (MP) methods are a promising class of feature construction algorithms for value function approximation. Yet existing MP methods require creating a pool of potential features, mandating expert knowledge or enumeration of a large feature pool, both of which hinder scalability. This pa...

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Bibliographic Details
Main Authors: Geramifard, Alborz, Walsh, Thomas J., Roy, Nicholas, How, Jonathan P.
Other Authors: Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Format: Article
Language:en_US
Published: Association for Uncertainty in Artificial Intelligence (AUAI) 2015
Online Access:http://hdl.handle.net/1721.1/97035
https://orcid.org/0000-0001-8576-1930
https://orcid.org/0000-0002-2508-1957
https://orcid.org/0000-0002-8293-0492

Internet

http://hdl.handle.net/1721.1/97035
https://orcid.org/0000-0001-8576-1930
https://orcid.org/0000-0002-2508-1957
https://orcid.org/0000-0002-8293-0492

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