Cart (Loading....) | Create Account
Close category search window
 

Limitation of Markov models and event-based learning and optimization

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)
Xi-Ren Cao ; Dept. of Electron. & Comput. Eng., Hong Kong Univ. of Sci. & Technol., kowloon

We first illustrate the possible limitations of the widely-used Markov model and then introduce the concepts of events, event-based policies and event-based optimization. Compared with the state-based policies, event-based policies may utilize the ldquofuturerdquo information and therefore may perform better. In addition, the number of events may scale to the system size while the number of states grows exponentially. The event-based approach is particularly efficient for systems with special structural properties. The solutions to the event-based optimization can be developed with a sensitivity-based view, which is developed recently for the area of stochastic learning and optimization.

Published in:

Control and Decision Conference, 2008. CCDC 2008. Chinese

Date of Conference:

2-4 July 2008

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.