DocumentCode
2809878
Title
A neural network which learns psychological internal representations
Author
Lee, Michael D.
Author_Institution
Dept. of Electr. & Electron. Eng., Adelaide Univ., SA, Australia
fYear
1996
fDate
18-20 Nov 1996
Firstpage
182
Lastpage
185
Abstract
A neural network model is described which learns psychological internal representations of a set of objects in its environment. The model adopts the `Psychological Space´ theoretical construct as an appropriate model of human mental representational structure. By considering mental representations as environmental adaptations, the model internally derives the indices of psychological similarity required to construct Psychological Spaces from information provided by the environment
Keywords
learning (artificial intelligence); neural nets; Psychological Spaces; environmental adaptations; human mental representational structure; mental representations; neural network; psychological internal representations; psychological similarity; Animal structures; Australia; Humans; Information processing; Multidimensional systems; Neural networks; Psychology; Sensor arrays; Sensor phenomena and characterization; Signal processing;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Information Systems, 1996., Australian and New Zealand Conference on
Conference_Location
Adelaide, SA
Print_ISBN
0-7803-3667-4
Type
conf
DOI
10.1109/ANZIIS.1996.573928
Filename
573928
Link To Document