Explanation-Based Neural Network Learning

Sebastian Thrun

ISBN 10: 1461285976 / ISBN 13: 9781461285977

Verlag: Springer US, Springer New York Okt 2011, 2011

Beschreibung

This item is printed on demand - Print on Demand Titel. Neuware -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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 284 pp. Englisch.

Bestandsnummer des Verkäufers 9781461285977

Bibliografische Details

• Titel: Explanation-Based Neural Network Learning
• Verlag: Springer US, Springer New York Okt 2011
• Erscheinungsjahr: 2011
• Sprache: Englisch
• ISBN-10: 1461285976
• ISBN-13: 9781461285977
• Einband: Taschenbuch
• Zustand: Neu
• Abmessungen: 235B x 155 H x 16 T Millimeter Breite: 235 mm, Höhe: 155 mm, Tiefe: 16 mm
• Gewicht: 435 Gramm

Über diesen Titel

Inhaltsangabe

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.