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A Cognitive Model of Concept Learning with a Flexible Internal Representation System.

Authors :
Hutchison, David
Kanade, Takeo
Kittler, Josef
Kleinberg, Jon M.
Mattern, Friedemann
Mitchell, John C.
Naor, Moni
Nierstrasz, Oscar
Rangan, C. Pandu
Steffen, Bernhard
Sudan, Madhu
Terzopoulos, Demetri
Tygar, Doug
Vardi, Moshe Y.
Weikum, Gerhard
Derong Liu
Shumin Fei
Zeng-Guang Hou
Huaguang Zhang
Changyin Sun
Source :
Advances in Neural Networks: ISNN 2007 (9783540723820); 2007, p1135-1143, 9p
Publication Year :
2007

Abstract

In the human mind, high-order knowledge is categorically organized, yet the nature of its internal representation system is not well understood. While it has been traditionally considered that there is a single innate representation system in our mind, recent studies suggest that the representational system is a dynamic, capable of adjusting a representation scheme to meet situational characteristics. In the present paper, we introduce a new cognitive modeling framework accounting for the flexibility in representing high-order category knowledge. Our modeling framework flexibly learns to adjust its internal knowledge representation scheme using a meta-heuristic optimization method. It also accounts for the multi-objective and the multi-notion natures of human learning, both of which are indicated as very important but often overlooked characteristics of human cognition. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISBNs :
9783540723820
Database :
Complementary Index
Journal :
Advances in Neural Networks: ISNN 2007 (9783540723820)
Publication Type :
Book
Accession number :
33176524
Full Text :
https://doi.org/10.1007/978-3-540-72383-7_133