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Logic for Learning : Learning Comprehensible Theories from Structured Data
Overview
This book provides an approach to knowledge representation, computation, and learning using higher-order logic. It is aimed at researchers, graduate students, and senior undergraduates working in computational logic and/or machine learning.
This item is Non-Returnable
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Details
- ISBN-13: 9783540420279
- ISBN-10: 3540420274
- Publisher: Springer
- Publish Date: August 2003
- Dimensions: 9.42 x 6.42 x 0.81 inches
- Shipping Weight: 1.15 pounds
- Page Count: 257
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