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

A memory-based neural network model for efficient adaptation to dynamic environments

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

2 Author(s)
Ozawa, S. ; Graduate Sch. of Sci. & Technol., Kobe Univ., Japan ; Tsumori, K.

When environments are dynamically varied for agents, the knowledge acquired from an environment would be useless in the future environments. Thus, agents should be able to not only acquire new knowledge but also modify old knowledge in learning. However, modifying all acquired knowledge is not always efficient. Because the knowledge once acquired may be useful again when the same (or similar) environment reappears. Moreover, some of the knowledge can be shared among different environments. To learn efficiently in such a situation, we propose a neural network model that consists of the following four modules: resource allocating network, long-term memory, association buffer, and environmental change detector. We apply this model to a simple dynamic environment in which several target functions to be approximated are varied in turn.

Published in:

Fuzzy Systems, 2004. Proceedings. 2004 IEEE International Conference on  (Volume:1 )

Date of Conference:

25-29 July 2004

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.