A chunking mechanism in a neural system for the parallel processing of a propositional production rules
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 chun...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 1995 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2099/2466 |
| Acceso en línea: | https://hdl.handle.net/2099/2466 |
| Access Level: | acceso abierto |
| Palabra clave: | Neural systems Rule-based knowledge Chunking mechanism Xarxes neuronals (Informàtica) Classificació AMS::68 Computer science::68Q Theory of computing |
| Sumario: | 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. |
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