Referenced Items are not available for this document.
A fuzzy inference model for learning from experiences (FILE) is proposed. the model can learn from experience data obtained by trial-and-error of a task and it can stably learn from both experiences of success and failure of a trial. the learning of the model is executed after each of trial of the task. hence, it is expected that the achievement rate increases with repetition of the trials, and that the model adapts to change of environment. in this paper, we confirm performance of the model by applying the model to a robot navigation task simulation and investigate the knowledge acquired by the learning
Published in:
Computational Intelligence for Modelling, Control and Automation, 2005 and International Conference on Intelligent Agents, Web Technologies and Internet Commerce, International Conference on
(Volume:1
)
Date of Conference: 28-30 Nov. 2005
- Page(s):
- 577 - 582
- Print ISBN:
- 0-7695-2504-0
- INSPEC Accession Number:
- 9109249
- Conference Location :
- Vienna
- Digital Object Identifier :
- 10.1109/CIMCA.2005.1631325
- Product Type:
- Conference Publications
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 2013 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.
