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 (Contributor), Walsh, Thomas J. (Contributor), Roy, Nicholas (Contributor), How, Jonathan P. (Contributor)
Other Authors: Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory (Contributor), Massachusetts Institute of Technology. Department of Aeronautics and Astronautics (Contributor), Massachusetts Institute of Technology. Laboratory for Information and Decision Systems (Contributor)
Format: Article
Language:English
Published: Association for Uncertainty in Artificial Intelligence (AUAI), 2015-05-19T18:41:05Z.
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