A unified framework for temporal difference methods

We propose a unified framework for a broad class of methods to solve projected equations that approximate the solution of a high-dimensional fixed point problem within a subspace S spanned by a small number of basis functions or features. These methods originated in approximate dynamic programming (...

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Bibliographic Details
Main Author: Bertsekas, Dimitri P. (Contributor)
Other Authors: Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science (Contributor), Massachusetts Institute of Technology. Laboratory for Information and Decision Systems (Contributor)
Format: Article
Language:English
Published: Institute of Electrical and Electronics Engineers, 2010-10-01T18:17:46Z.
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Description
Summary:We propose a unified framework for a broad class of methods to solve projected equations that approximate the solution of a high-dimensional fixed point problem within a subspace S spanned by a small number of basis functions or features. These methods originated in approximate dynamic programming (DP), where they are collectively known as temporal difference (TD) methods. Our framework is based on a connection with projection methods for monotone variational inequalities, which involve alternative representations of the subspace S (feature scaling). Our methods admit simulation-based implementations, and even when specialized to DP problems, include extensions/new versions of the standard TD algorithms, which offer some special implementation advantages and reduced overhead.
National Science Foundation (U.S.) (NSF grant ECCS-0801549)