By Topic

A unified framework for temporal difference methods

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

1 Author(s)
Bertsekas, D.P. ; Lab. for Inf. & Decision Syst. (LIDS), Massachusetts Inst. of Technol., Cambridge, MA

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.

Published in:

Adaptive Dynamic Programming and Reinforcement Learning, 2009. ADPRL '09. IEEE Symposium on

Date of Conference:

March 30 2009-April 2 2009