By Topic

Incremental Value Iteration for Time-Aggregated Markov-Decision Processes

Sign In

Full text access may be available.

To access full text, please use your member or institutional sign in.

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

3 Author(s)
Tao Sun ; Tsinghua Univ., Beijing ; Qianchuan Zhao ; Luh, P.B.

A value iteration algorithm for time-aggregated Markov-decision processes (MDPs) is developed to solve problems with large state spaces. The algorithm is based on a novel approach which solves a time aggregated MDP by incrementally solving a set of standard MDPs. Therefore, the algorithm converges under the same assumption as standard value iteration. Such assumption is much weaker than that required by the existing time aggregated value iteration algorithm. The algorithms developed in this paper are also applicable to MDPs with fractional costs.

Published in:

Automatic Control, IEEE Transactions on  (Volume:52 ,  Issue: 11 )