Explanation-Based Neural Network Learning
Subtitle: a Lifelong Learning Approach
By: by Sebastian Thrun
Series: The Kluwer International Series in Engineering and Computer Science, Knowledge Representation, Learning and Expert Systems -- 357; Kluwer international series in engineering and computer science -- 357.
Publisher: Springer US
Published: 1996
Place of publication: Boston, MA
Language: eng
Format: [electronic resource] :
Number of pages: 280
ISBN-13: 9781461285977; 9781461313816
Subjects: Computer science; Artificial intelligence
Description: 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.
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