Explanation-Based Neural Network Learning: A Lifelong Learning Approach The Kluwer International Series in Engineering and Computer Science

Thrun, Sebastian:

ISBN 10: 0792397169 / ISBN 13: 9780792397168

Edité par Kluwer Academic Publishers, 1996

A propos de cet article

264 Seiten Der Erhaltungszustand des hier angebotenen Werks ist trotz seiner Bibliotheksnutzung sehr sauber. Es befindet sich lediglich ein Bibliotheksstempel im Buch; ordnungsgemäß entwidmet. Sprache: Englisch Gewicht in Gramm: 670.

N° de réf. du vendeur 1455540

Détails bibliographiques

• Titre: Explanation-Based Neural Network Learning: A Lifelong Learning Approach The Kluwer International Series in Engineering and Computer Science
• Éditeur: Kluwer Academic Publishers
• Date de parution: 1996
• Langue: anglais
• ISBN à 10 chiffres: 0792397169
• ISBN à 13 chiffres: 9780792397168
• Reliure: gebundene Ausgabe
• État de l'article: Gut
• Poids: 670 grammes
• Catalogues du vendeur:
  • 90 Varia

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Synopsis

Lifelong learning addresses situations in which a learner faces a series of different learning tasks providing the opportunity for synergy among them. Explanation-based neural network learning (EBNN) is a machine learning algorithm that transfers knowledge across multiple learning tasks. When faced with a new learning task, EBNN exploits domain knowledge accumulated in previous learning tasks to guide generalization in the new one. As a result, EBNN generalizes more accurately from less data than comparable methods. Explanation-Based Neural Network Learning: A Lifelong Learning Approach describes the basic EBNN paradigm and investigates it in the context of supervised learning, reinforcement learning, robotics, and chess.
`The paradigm of lifelong learning - using earlier learned knowledge to improve subsequent learning - is a promising direction for a new generation of machine learning algorithms. Given the need for more accurate learning methods, it is difficult to imagine a future for machine learning that does not include this paradigm.'
From the Foreword by Tom M. Mitchell.