An agent-based approach to ANN training

被引：13
|
作者：
Czarnowski, I. [1 ]
Jedrzejowicz, P. [1 ]
机构：
[1] Gdynia Maritime Univ, Dept Informat Syst, PL-81225 Gdynia, Poland
来源：
KNOWLEDGE-BASED SYSTEMS | 2006年 / 19卷 / 05期
关键词：
neural networks training; agent-based approach; optimization; multi-agent systems;
D O I：
10.1016/j.knosys.2005.11.012
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, a team of agents applied to train a feed-forward artificial neural networks is proposed, implemented and experimentally evaluated. The approach is based on a new variant of the A-Team architecture. Each agent member of the team is executing its own simple training procedure and it is expected that the whole team demonstrates complex collective behavior. The paper includes a description of the proposed approach and presents the results of the experiment involving benchmark datasets. The results show that the approach could be considered as a competitive training tool. (c) 2006 Elsevier B.V. All rights reserved.
引用
收藏
页码：304 / 308
页数：5
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