このエントリーをはてなブックマークに追加
ID 30129
FullText URL
Author
Abstract

In this paper, we propose a new double-layered state space construction method, which consists of Fritzke's Growing Neural Gas algorithm and a class management mechanism of GNG units. The classification algorithm yields a new class by referring to anticipation error, anticipation vectors of an originated class, and anticipation vectors GNG units belonging in the originated class.

Keywords
Reinforcement Learning
Growing Neural Gas
Incremental State Space Construction
Note
Published with permission from the copyright holder. This is the institute's copy, as published in SICE 2004 Annual Conference, 4-6 Aug. 2004, Vol. 3, Pages 2698-2703.
Publisher URL:http://ieeexplore.ieee.org/search/wrapper.jsp?arnumber=1491910
Copyright © 2004 IEEE. All rights reserved.
Published Date
2004-8
Publication Title
SICE 2004 Annual Conference
Volume
volume3
Start Page
2698
End Page
2703
Content Type
Journal Article
language
English
Refereed
True
Submission Path
industrial_engineering/19