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| Natura: | Artículo científico |
| Lingua: | en |
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Asociación Española para la Inteligencia Artificial
2017
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| Accesso online: | https://www.redalyc.org/articulo.oa?id=92553915005 |
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| _version_ | 1866811921850695680 |
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| author | Fernando Martínez-Plumed |
| author_facet | Fernando Martínez-Plumed |
| contents | Incremental and developmental perspectives for general-purpose learning systems Fernando Martínez-Plumed Ingeniería general forgetting task difficulty intelligence tests inductive programming The stupefying success of Artificial Intelligence (AI) for specific problems, from recommender systems to self-driving cars, has not yet been matched with a similar progress in general AI systems, coping with a variety of (different) problems. This dissertation deals with the long-standing problem of creating more general AI systems, through the analysis of their development and the evaluation of their cognitive abilities. It presents a declarative general-purpose learning system and a developmental and lifelong approach for knowledge acquisition, consolidation and forgetting. It also analyses the use of the use of more ability-oriented evaluation techniques for AI evaluation and provides further insight for the understanding of the concepts of development and incremental learning in AI systems. 2017 artículo científico 1137-3601 https://www.redalyc.org/articulo.oa?id=92553915005 en http://www.redalyc.org/revista.oa?id=925 Inteligencia Artificial. Revista Iberoamericana de Inteligencia Artificial application/pdf Asociación Española para la Inteligencia Artificial Inteligencia Artificial. Revista Iberoamericana de Inteligencia Artificial (España) Num.60 Vol.20 |
| format | Artículo científico |
| id | redalyc_92553915005 |
| language | en |
| publishDate | 2017 |
| publisher | Asociación Española para la Inteligencia Artificial |
| spellingShingle | Incremental and developmental perspectives for general-purpose learning systems Fernando Martínez-Plumed Ingeniería general forgetting task difficulty intelligence tests inductive programming Incremental and developmental perspectives for general-purpose learning systems Fernando Martínez-Plumed Ingeniería general forgetting task difficulty intelligence tests inductive programming The stupefying success of Artificial Intelligence (AI) for specific problems, from recommender systems to self-driving cars, has not yet been matched with a similar progress in general AI systems, coping with a variety of (different) problems. This dissertation deals with the long-standing problem of creating more general AI systems, through the analysis of their development and the evaluation of their cognitive abilities. It presents a declarative general-purpose learning system and a developmental and lifelong approach for knowledge acquisition, consolidation and forgetting. It also analyses the use of the use of more ability-oriented evaluation techniques for AI evaluation and provides further insight for the understanding of the concepts of development and incremental learning in AI systems. 2017 artículo científico 1137-3601 https://www.redalyc.org/articulo.oa?id=92553915005 en http://www.redalyc.org/revista.oa?id=925 Inteligencia Artificial. Revista Iberoamericana de Inteligencia Artificial application/pdf Asociación Española para la Inteligencia Artificial Inteligencia Artificial. Revista Iberoamericana de Inteligencia Artificial (España) Num.60 Vol.20 |
| title | Incremental and developmental perspectives for general-purpose learning systems |
| topic | Ingeniería general forgetting task difficulty intelligence tests inductive programming |
| url | https://www.redalyc.org/articulo.oa?id=92553915005 |