Autoassociator networks: insights into infant cognition

In this: publication
By this: publisher
In this Subject: Psychology
By this author: Sirois S.

Author: Sirois S.

Source: Developmental Science, Volume 7, Number 2, April 2004 , pp. 133-140(8)

Buy & download fulltext article:

Price: $48.00 plus tax (Refund Policy)

Abstract:

This paper presents autoassociator neural networks. A first section reviews the architecture of these models, common learning rules, and presents sample simulations to illustrate their abilities. In a second section, the ability of these models to account for learning phenomena such as habituation is reviewed. The contribution of these networks to discussions about infant cognition is highlighted. A new, modular approach is presented in a third section. In the discussion, a role for these learning models in a broader developmental framework is proposed.

Document Type: Research article

DOI: http://dx.doi.org/10.1111/j.1467-7687.2004.00330.x

Publication date: 2004-04-01