A chunking mechanism in a neural system for the parallel processing of a propositional production rules
Visualitza/Obre
Estadístiques de LA Referencia / Recolecta
Inclou dades d'ús des de 2022
Cita com:
hdl:2099/2466
Tipus de documentArticle
Data publicació1995
EditorUniversitat Politècnica de Catalunya. Secció de Matemàtiques i Informàtica
Condicions d'accésAccés obert
Llevat que s'hi indiqui el contrari, els
continguts d'aquesta obra estan subjectes a la llicència de Creative Commons
:
Reconeixement-NoComercial-SenseObraDerivada 3.0 Espanya
Abstract
The problem of extracting more compact rules from a rule-based knowledge base is approached by means of a chunking mechanism implemented via a neural system. Taking advantage of the parallel processing potentialities of neural systems, the computational problem normally arising when introducing chuncking processes is overcome. Also the memory saturation effect is coped with using some sort of "forgetting" mechanism which allows the system to eliminate previously stored, but less often used chunks. Even though some connection weights are changed in the process of storing or discarding chunks, we emphasize that this neural system cannot be regarded as a "connectionist" system, since a localist semantic interpretation is adopted and no classical learning algorithm is employed.
ISSN1134-5632
Col·leccions
Fitxers | Descripció | Mida | Format | Visualitza |
---|---|---|---|---|
pasco.pdf | 206,8Kb | Visualitza/Obre |