Readers of this list may be interested in the following article that was
just published in JAIR:
Zhang, N.L. and Zhang, W. (2001)
"Speeding Up the Convergence of Value Iteration in Partially Observable
Markov
Decision Processes", Volume 14, pages 29-51.
Available in HTML, PDF, PostScript and compressed PostScript.
For quick access via your WWW browser, use this URL:
http://www.jair.org/abstracts/zhang01a.html
More detailed instructions are below.
Abstract: Partially observable Markov decision processes (POMDPs) have
recently become popular among many AI researchers because they serve
as a natural model for planning under uncertainty. Value iteration is
a well-known algorithm for finding optimal policies for POMDPs. It
typically takes a large number of iterations to converge. This paper
proposes a method for accelerating the convergence of value iteration.
The method has been evaluated on an array of benchmark problems and
was found to be very effective: It enabled value iteration to converge
after only a few iterations on all the test problems.
The article is available via:
-- comp.ai.jair.papers (also see comp.ai.jair.announce)
-- World Wide Web: The URL for our World Wide Web server is
http://www.jair.org/
For direct access to this article and related files try:
http://www.jair.org/abstracts/zhang01a.html
-- Anonymous FTP from either of the two sites below.
Carnegie-Mellon University (USA):
ftp://ftp.cs.cmu.edu/project/jair/volume14/zhang01a.ps
The University of Genoa (Italy):
ftp://ftp.mrg.dist.unige.it/pub/jair/pub/volume14/zhang01a.ps
The compressed PostScript file is named zhang01a.ps.Z (138K)
For more information about JAIR, visit our WWW or FTP sites, or
contact [EMAIL PROTECTED]
Steven Minton
CTO, Fetch Technologies (www.fetch.com)
310-448-8275
