Explanation-Based Neural Network Learning : A Lifelong Learning Approach PDF
by Sebastian Thrun
Part of the The Springer International Series in Engineering and Computer Science series
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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 LearningApproach 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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- Format:PDF
- Publisher:Springer US
- Publication Date:06/12/2012
- Category:
- ISBN:9781461313816
Information
-
Download Now
- Format:PDF
- Publisher:Springer US
- Publication Date:06/12/2012
- Category:
- ISBN:9781461313816