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Explanation-Based Neural Network Learning: A Lifelong Learning Approach
     

Explanation-Based Neural Network Learning: A Lifelong Learning Approach

by Sebastian Thrun
 

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

Overview

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.

Product Details

ISBN-13:
9781461285977
Publisher:
Springer US
Publication date:
07/31/2012
Series:
The Springer International Series in Engineering and Computer Science , #357
Edition description:
Softcover reprint of the original 1st ed. 1996
Pages:
264
Product dimensions:
6.14(w) x 9.21(h) x 0.60(d)

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