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Item Details
Title:
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LOGIC FOR LEARNING
LEARNING COMPREHENSIBLE THEORIES FROM STRUCTURED DATA |
By: |
J. W. Lloyd |
Format: |
Hardback |
List price:
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£45.99 |
We currently do not stock this item, please contact the publisher directly for
further information.
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ISBN 10: |
3540420274 |
ISBN 13: |
9783540420279 |
Publisher: |
SPRINGER-VERLAG BERLIN AND HEIDELBERG GMBH & CO. KG |
Series: |
Cognitive Technologies |
Pages: |
257 |
Description: |
Provides a framework for knowledge representation and computation based on higher-order logic, and demonstrates its advantages over more standard approaches based on first-order logic. This book explains how higher-order logic provides suitable knowledge representation formalisms and hypothesis languages for machine learning applications. |
Synopsis: |
This book provides a systematic approach to knowledge representation, computation, and learning using higher-order logic. For those interested in computational logic, it provides a framework for knowledge representation and computation based on higher-order logic, and demonstrates its advantages over more standard approaches based on first-order logic. For those interested in machine learning, the book explains how higher-order logic provides suitable knowledge representation formalisms and hypothesis languages for machine learning applications. |
Illustrations: |
biography |
Publication: |
Germany |
Imprint: |
Springer-Verlag Berlin and Heidelberg GmbH & Co. K |
Returns: |
Returnable |
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Ramadan and Eid al-Fitr
A celebratory, inclusive and educational exploration of Ramadan and Eid al-Fitr for both children that celebrate and children who want to understand and appreciate their peers who do.
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