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Toward Robots That Reason: Logic, Probability & Causal Laws (Synthesis Lectures on Artificial Intelligence and Machine Learning) - Tapa dura
Sinopsis
This book discusses the two fundamental elements that underline the science and design of artificial intelligence (AI) systems: the learning and acquisition of knowledge from observational data, and the reasoning of that knowledge together with whatever information is available about the application at hand. It then presents a mathematical treatment of the core issues that arise when unifying first-order logic and probability, especially in the presence of dynamics, including physical actions, sensing actions and their effects. A model for expressing causal laws describing dynamics is also considered, along with computational ideas for reasoning with such laws over probabilistic logical knowledge.
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Acerca del autor
Vaishak Belle, Ph.D., is a Chancellor’s Fellow and Reader at The University of Edinburgh School of Informatics. He is also an Alan Turing Institute Faculty Fellow, a Royal Society University Research Fellow, and a member of the Royal Society of Edinburgh’s Young Academy of Scotland. Dr. Belle directs a research lab on artificial intelligence at The University of Edinburgh, specializing in the unification of symbolic logic and machine learning. He has co-authored over 50 scientific articles on AI, and has won several best paper awards.
De la contraportada
This book discusses the two fundamental elements that underline the science and design of artificial intelligence (AI) systems: the learning and acquisition of knowledge from observational data, and the reasoning of that knowledge together with whatever information is available about the application at hand. It then presents a mathematical treatment of the core issues that arise when unifying first-order logic and probability, especially in the presence of dynamics, including physical actions, sensing actions and their effects. A model for expressing causal laws describing dynamics is also considered, along with computational ideas for reasoning with such laws over probabilistic logical knowledge.
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- EditorialSpringer-Verlag GmbH
- Año de publicación2023
- ISBN 10 3031210026
- ISBN 13 9783031210020
- EncuadernaciónTapa dura
- IdiomaInglés
- Número de páginas204
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Toward Robots That Reason: Logic, Probability & Causal Laws
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Springer International Publishing, 2023
ISBN 10: 3031210026
ISBN 13: 9783031210020
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Librería: Buchpark, Trebbin, Alemania
Calificación del vendedor: 5 de 5 estrellas
Condición: Hervorragend. Zustand: Hervorragend | Seiten: 204 | Sprache: Englisch | Produktart: Bücher. Nº de ref. del artículo: 41491809/1
Cantidad disponible: 1 disponibles
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Toward Robots That Reason: Logic, Probability & Causal Laws
Publicado por
Springer International Publishing, 2023
ISBN 10: 3031210026
ISBN 13: 9783031210020
Antiguo o usado
Tapa dura
Librería: Buchpark, Trebbin, Alemania
Calificación del vendedor: 5 de 5 estrellas
Condición: Sehr gut. Zustand: Sehr gut | Seiten: 204 | Sprache: Englisch | Produktart: Bücher. Nº de ref. del artículo: 41491809/2
Cantidad disponible: 1 disponibles
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Toward Robots That Reason: Logic, Probability & Causal Laws
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Springer International Publishing Feb 2023, 2023
ISBN 10: 3031210026
ISBN 13: 9783031210020
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Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
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Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book discusses the two fundamental elements that underline the science and design of artificial intelligence (AI) systems: the learning and acquisition of knowledge from observational data, and the reasoning of that knowledge together with whatever information is available about the application at hand. It then presents a mathematical treatment of the core issues that arise when unifying first-order logic and probability, especially in the presence of dynamics, including physical actions, sensing actions and their effects. A model for expressing causal laws describing dynamics is also considered, along with computational ideas for reasoning with such laws over probabilistic logical knowledge. 204 pp. Englisch. Nº de ref. del artículo: 9783031210020
Cantidad disponible: 2 disponibles
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Toward Robots That Reason: Logic, Probability & Causal Laws
Publicado por
Springer International Publishing, 2023
ISBN 10: 3031210026
ISBN 13: 9783031210020
Nuevo
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Librería: AHA-BUCH GmbH, Einbeck, Alemania
Calificación del vendedor: 5 de 5 estrellas
Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book discusses the two fundamental elements that underline the science and design of artificial intelligence (AI) systems: the learning and acquisition of knowledge from observational data, and the reasoning of that knowledge together with whatever information is available about the application at hand. It then presents a mathematical treatment of the core issues that arise when unifying first-order logic and probability, especially in the presence of dynamics, including physical actions, sensing actions and their effects. A model for expressing causal laws describing dynamics is also considered, along with computational ideas for reasoning with such laws over probabilistic logical knowledge. Nº de ref. del artículo: 9783031210020
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Toward Robots That Reason: Logic, Probability & Causal Laws
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Springer, Berlin|Springer International Publishing|Springer, 2023
ISBN 10: 3031210026
ISBN 13: 9783031210020
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Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book discusses the two fundamental elements that underline the science and design of artificial intelligence (AI) systems: the learning and acquisition of knowledge from observational data, and the reasoning of that knowledge together with whatever inf. Nº de ref. del artículo: 732828435
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Toward Robots That Reason: Logic, Probability & Causal Laws
Publicado por
Springer International Publishing, Springer International Publishing Feb 2023, 2023
ISBN 10: 3031210026
ISBN 13: 9783031210020
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Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
Calificación del vendedor: 5 de 5 estrellas
Buch. Condición: Neu. Neuware -This book discusses the two fundamental elements that underline the science and design of artificial intelligence (AI) systems: the learning and acquisition of knowledge from observational data, and the reasoning of that knowledge together with whatever information is available about the application at hand. It then presents a mathematical treatment of the core issues that arise when unifying first-order logic and probability, especially in the presence of dynamics, including physical actions, sensing actions and their effects. A model for expressing causal laws describing dynamics is also considered, along with computational ideas for reasoning with such laws over probabilistic logical knowledge.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 204 pp. Englisch. Nº de ref. del artículo: 9783031210020
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