Cognitive Science Based Machine Learning Architecture

Document Type: 
Article
Article Type: 
Other
Disciplines: 
Psychology
Topics: 
Cognition
Deposited by: 
Prof Stan Franklin
Date of Issue: 
2006
Authors: 
Sidney D’Mello, Stan Franklin, Uma Ramamurthy, Bernard Baars
Journal/Publication Title: 
American Association for Artificial Intelligence
Series Name: 
AAAI 2006 Spring Symposium Series
Publisher: 
Stanford University
Place of Publication: 
Palo Alto, California, USA
Official URL: 
http://ccrg.cs.memphis.edu/assets/papers/SS0602DMelloS.pdf
Abstract: 
In an attempt to illustrate the application of cognitive science principles to hard AI problems in machine learning we propose the LIDA technology, a cognitive science based architecture capable of more human-like learning. A LIDA based software agent or cognitive robot will be capable of three fundamental, continuously active, humanlike learning mechanisms:1) perceptual learning, the learning of new objects, categories, relations, etc., 2) episodic learning of events, the what, where, and when, 3) procedural learning, the learning of new actions and action sequences with which to accomplish new tasks. The paper argues for the use of modular components, each specializing in implementing individual facets of human and animal cognition, as a viable approach towards achieving general intelligence.
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