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Learning without limits: from problem solving towards a Unified Theory of Learning

Taatgen, Niels (1999) Learning without limits: from problem solving towards a Unified Theory of Learning. [Thesis]

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Abstract

Learning is usually studied on the basis of binary distinctions like implicit vs. explicit learning, using instance vs. using rules, connectionist vs. symbolist, etc. In this thesis it is argued that many of these distinctions are not useful at all in understanding learning. This statement is supported by a large set of models in ACT-R, a cognitive architecture developed by J.R. Anderson. These models demonstrate that deeper understanding is often gained when the traditional distinctions are ignored.

Item Type:Thesis
Keywords:cognitive modeling, ACT-R, skill acquisition, learning, implicit learning, explicit learning, scheduling, insight
Subjects:Psychology > Cognitive Psychology
Computer Science > Artificial Intelligence
Computer Science > Complexity Theory
Computer Science > Machine Learning
Psychology > Developmental Psychology
ID Code:1021
Deposited By:Taatgen, Niels
Deposited On:16 Oct 2000
Last Modified:11 Mar 2011 08:54

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