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Neural-Symbolic Cognitive Reasoning
Taschenbuch von Artur S. D'Avila Garcez (u. a.)
Sprache: Englisch

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Beschreibung
Humans are often extraordinary at performing practical reasoning. There are cases where the human computer, slow as it is, is faster than any artificial intelligence system. Are we faster because of the way we perceive knowledge as opposed to the way we represent it?

The authors address this question by presenting neural network models that integrate the two most fundamental phenomena of cognition: our ability to learn from experience, and our ability to reason from what has been learned. This book is the first to offer a self-contained presentation of neural network models for a number of computer science logics, including modal, temporal, and epistemic logics. By using a graphical presentation, it explains neural networks through a sound neural-symbolic integration methodology, and it focuses on the benefits of integrating effective robust learning with expressive reasoning capabilities.

The book will be invaluable reading for academic researchers, graduate students, and senior undergraduates in computer science, artificial intelligence, machine learning, cognitive science and engineering. It will also be of interest to computational logicians, and professional specialists on applications of cognitive, hybrid and artificial intelligence systems.
Humans are often extraordinary at performing practical reasoning. There are cases where the human computer, slow as it is, is faster than any artificial intelligence system. Are we faster because of the way we perceive knowledge as opposed to the way we represent it?

The authors address this question by presenting neural network models that integrate the two most fundamental phenomena of cognition: our ability to learn from experience, and our ability to reason from what has been learned. This book is the first to offer a self-contained presentation of neural network models for a number of computer science logics, including modal, temporal, and epistemic logics. By using a graphical presentation, it explains neural networks through a sound neural-symbolic integration methodology, and it focuses on the benefits of integrating effective robust learning with expressive reasoning capabilities.

The book will be invaluable reading for academic researchers, graduate students, and senior undergraduates in computer science, artificial intelligence, machine learning, cognitive science and engineering. It will also be of interest to computational logicians, and professional specialists on applications of cognitive, hybrid and artificial intelligence systems.
Zusammenfassung

Humans are often extraordinary at performing practical reasoning. There are cases where the human computer, slow as it is, is faster than any artificial intelligence system. Are we faster because of the way we perceive knowledge as opposed to the way we represent it? The authors address this question by presenting neural network models that integrate the two most fundamental phenomena of cognition: our ability to learn from experience, and our ability to reason from what has been learned. This book is the first to offer a self-contained presentation of neural network models for a number of computer science logics, including modal, temporal, and epistemic logics, by using a graphical presentation. It explains neural networks using a sound, neural-symbolic integration methodology, and it focuses on the benefits of integrating effective robust learning with expressive reasoning capability.

Inhaltsverzeichnis
Logic and Knowledge Representation.- Artificial Neural Networks.- Neural-Symbolic Learning Systems.- Connectionist Modal Logic.- Connectionist Temporal Reasoning.- Connectionist Intuitionistic Reasoning.- Applications of Connectionist Nonclassical Reasoning.- Fibring Neural Networks.- Relational Learning in Neural Networks.- Argumentation Frameworks as Neural Networks.- Reasoning about Probabilities in Neural Networks.- Conclusions.
Details
Erscheinungsjahr: 2010
Genre: Informatik
Rubrik: Naturwissenschaften & Technik
Medium: Taschenbuch
Seiten: 212
Reihe: Cognitive Technologies
Inhalt: xiv
198 S.
53 s/w Illustr.
198 p. 53 illus.
ISBN-13: 9783642092299
ISBN-10: 3642092292
Sprache: Englisch
Ausstattung / Beilage: Paperback
Einband: Kartoniert / Broschiert
Autor: D'Avila Garcez, Artur S.
Gabbay, Dov M.
Lamb, Luís C.
Auflage: Softcover reprint of hardcover 1st ed. 2009
Hersteller: Springer Berlin
Springer Berlin Heidelberg
Cognitive Technologies
Maße: 235 x 155 x 12 mm
Von/Mit: Artur S. D'Avila Garcez (u. a.)
Erscheinungsdatum: 18.11.2010
Gewicht: 0,33 kg
preigu-id: 107212046
Zusammenfassung

Humans are often extraordinary at performing practical reasoning. There are cases where the human computer, slow as it is, is faster than any artificial intelligence system. Are we faster because of the way we perceive knowledge as opposed to the way we represent it? The authors address this question by presenting neural network models that integrate the two most fundamental phenomena of cognition: our ability to learn from experience, and our ability to reason from what has been learned. This book is the first to offer a self-contained presentation of neural network models for a number of computer science logics, including modal, temporal, and epistemic logics, by using a graphical presentation. It explains neural networks using a sound, neural-symbolic integration methodology, and it focuses on the benefits of integrating effective robust learning with expressive reasoning capability.

Inhaltsverzeichnis
Logic and Knowledge Representation.- Artificial Neural Networks.- Neural-Symbolic Learning Systems.- Connectionist Modal Logic.- Connectionist Temporal Reasoning.- Connectionist Intuitionistic Reasoning.- Applications of Connectionist Nonclassical Reasoning.- Fibring Neural Networks.- Relational Learning in Neural Networks.- Argumentation Frameworks as Neural Networks.- Reasoning about Probabilities in Neural Networks.- Conclusions.
Details
Erscheinungsjahr: 2010
Genre: Informatik
Rubrik: Naturwissenschaften & Technik
Medium: Taschenbuch
Seiten: 212
Reihe: Cognitive Technologies
Inhalt: xiv
198 S.
53 s/w Illustr.
198 p. 53 illus.
ISBN-13: 9783642092299
ISBN-10: 3642092292
Sprache: Englisch
Ausstattung / Beilage: Paperback
Einband: Kartoniert / Broschiert
Autor: D'Avila Garcez, Artur S.
Gabbay, Dov M.
Lamb, Luís C.
Auflage: Softcover reprint of hardcover 1st ed. 2009
Hersteller: Springer Berlin
Springer Berlin Heidelberg
Cognitive Technologies
Maße: 235 x 155 x 12 mm
Von/Mit: Artur S. D'Avila Garcez (u. a.)
Erscheinungsdatum: 18.11.2010
Gewicht: 0,33 kg
preigu-id: 107212046
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