The idea of this book is to establish a new scientific discipline, “noology,” under which a set of fundamental principles are proposed for the characterization of both naturally occurring and artificial intelligent systems.
The methodology adopted in Principles of Noology for the characterization of intelligent systems, or “noological systems,” is a computational one, much like that of AI. Many AI devices such as predicate logic representations, search mechanisms, heuristics, and computational learning mechanisms are employed but they are recast in a totally new framework for the characterization of noological systems. The computational approach in this book provides a quantitative and high resolution understanding of noological processes, and at the same time the principles and methodologies formulated are directly implementable in AI systems.
In contrast to traditional AI that ignores motivational and affective processes, under the paradigm of noology, motivational and affective processes are central to the functioning of noological systems and their roles in noological processes are elucidated in detailed computational terms. In addition, a number of novel representational and learning mechanisms are proposed, and ample examples and computer simulations are provided to show their applications. These include rapid effective causal learning (a novel learning mechanism that allows an AI/noological system to learn causality with a small number of training instances), learning of scripts that enables knowledge chunking and rapid problem solving, and learning of heuristics that further accelerates problem solving. Semantic grounding allows an AI/noological system to “truly understand” the meaning of the knowledge it encodes. This issue is extensively explored.
This is a highly informative book providing novel and deep insights into intelligent systems which is particularly relevant to both researchers and students of AI and the cognitive sciences.
"synopsis" may belong to another edition of this title.
The idea of this book is to establish a new scientific discipline, “noology,” under which a set of fundamental principles are proposed for the characterization of both naturally occurring and artificial intelligent systems.
The methodology adopted in Principles of Noology for the characterization of intelligent systems, or “noological systems,” is a computational one, much like that of AI. Many AI devices such as predicate logic representations, search mechanisms, heuristics, and computational learning mechanisms are employed but they are recast in a totally new framework for the characterization of noological systems. The computational approach in this book provides a quantitative and high resolution understanding of noological processes, and at the same time the principles and methodologies formulated are directly implementable in AI systems.
In contrast to traditional AI that ignores motivational and affective processes, under the paradigm of noology, motivational and affective processes are central to the functioning of noological systems and their roles in noological processes are elucidated in detailed computational terms. In addition, a number of novel representational and learning mechanisms are proposed, and ample examples and computer simulations are provided to show their applications. These include rapid effective causal learning (a novel learning mechanism that allows an AI/noological system to learn causality with a small number of training instances), learning of scripts that enables knowledge chunking and rapid problem solving, and learning of heuristics that further accelerates problem solving. Semantic grounding allows an AI/noological system to “truly understand” the meaning of the knowledge it encodes. This issue is extensively explored.
This is a highly informative book providing novel and deep insights into intelligent systems which is particularly relevant to both researchers and students of AI and the cognitive sciences.
"About this title" may belong to another edition of this title.
Seller: Universitätsbuchhandlung Herta Hold GmbH, Berlin, Germany
XIX, 431 p. Hardcover. Versand aus Deutschland / We dispatch from Germany via Air Mail. Einband bestoßen, daher Mängelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. Socio-Affective Computing. Vol. 3. Sprache: Englisch. Seller Inventory # 955KB
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Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The idea of this book is to establish a new scientific discipline, 'noology,' under which a set of fundamental principles are proposed for the characterization of both naturally occurring and artificial intelligent systems. The methodology adopted in Principles of Noology for the characterization of intelligent systems, or 'noological systems,' is a computational one, much like that of AI. Many AI devices such as predicate logic representations, search mechanisms, heuristics, and computational learning mechanisms are employed but they are recast in a totally new framework for the characterization of noological systems. The computational approach in this book provides a quantitative and high resolution understanding of noological processes, and at the same time the principles and methodologies formulated are directly implementable in AI systems.In contrast to traditional AI that ignores motivational and affective processes, under the paradigm of noology, motivational and affective processes are central to the functioning of noological systems and their roles in noological processes are elucidated in detailed computational terms. In addition, a number of novel representational and learning mechanisms are proposed, and ample examples and computer simulations are provided to show their applications. These include rapid effective causal learning (a novel learning mechanism that allows an AI/noological system to learn causality with a small number of training instances), learning of scripts that enables knowledge chunking and rapid problem solving, and learning of heuristics that further accelerates problem solving. Semantic grounding allows an AI/noological system to 'truly understand' the meaning of the knowledge it encodes. This issue is extensively explored.This is a highly informative book providing novel and deep insights into intelligent systems which is particularly relevant to both researchers and students of AI and the cognitive sciences. 452 pp. Englisch. Seller Inventory # 9783319321110
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Gebunden. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Provides novel and deep insights into intelligent systemsContains supplementary material which demonstrates examples and processesOffers the opportunity to learn techniques and methodologiesBrings readers quantitative and high resolu. Seller Inventory # 118772748
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Hardcover. Condition: new. Hardcover. The idea of this book is to establish a new scientific discipline, noology, under which a set of fundamental principles are proposed for the characterization of both naturally occurring and artificial intelligent systems. The methodology adopted in Principles of Noology for the characterization of intelligent systems, or noological systems, is a computational one, much like that of AI. Many AI devices such as predicate logic representations, search mechanisms, heuristics, and computational learning mechanisms are employed but they are recast in a totally new framework for the characterization of noological systems. The computational approach in this book provides a quantitative and high resolution understanding of noological processes, and at the same time the principles and methodologies formulated are directly implementable in AI systems.In contrast to traditional AI that ignores motivational and affective processes, under the paradigm of noology,motivational and affective processes are central to the functioning of noological systems and their roles in noological processes are elucidated in detailed computational terms. In addition, a number of novel representational and learning mechanisms are proposed, and ample examples and computer simulations are provided to show their applications. These include rapid effective causal learning (a novel learning mechanism that allows an AI/noological system to learn causality with a small number of training instances), learning of scripts that enables knowledge chunking and rapid problem solving, and learning of heuristics that further accelerates problem solving. Semantic grounding allows an AI/noological system to truly understand the meaning of the knowledge it encodes. This issue is extensively explored.This is a highly informative book providing novel and deep insights into intelligent systems which is particularly relevant to both researchers and students of AI and the cognitive sciences. These include rapid effective causal learning (a novel learning mechanism that allows an AI/noological system to learn causality with a small number of training instances), learning of scripts that enables knowledge chunking and rapid problem solving, and learning of heuristics that further accelerates problem solving. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9783319321110
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Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - The idea of this book is to establish a new scientific discipline, 'noology,' under which a set of fundamental principles are proposed for the characterization of both naturally occurring and artificial intelligent systems. The methodology adopted in Principles of Noology for the characterization of intelligent systems, or 'noological systems,' is a computational one, much like that of AI. Many AI devices such as predicate logic representations, search mechanisms, heuristics, and computational learning mechanisms are employed but they are recast in a totally new framework for the characterization of noological systems. The computational approach in this book provides a quantitative and high resolution understanding of noological processes, and at the same time the principles and methodologies formulated are directly implementable in AI systems.In contrast to traditional AI that ignores motivational and affective processes, under the paradigm of noology,motivational and affective processes are central to the functioning of noological systems and their roles in noological processes are elucidated in detailed computational terms. In addition, a number of novel representational and learning mechanisms are proposed, and ample examples and computer simulations are provided to show their applications. These include rapid effective causal learning (a novel learning mechanism that allows an AI/noological system to learn causality with a small number of training instances), learning of scripts that enables knowledge chunking and rapid problem solving, and learning of heuristics that further accelerates problem solving. Semantic grounding allows an AI/noological system to 'truly understand' the meaning of the knowledge it encodes. This issue is extensively explored.This is a highly informative book providing novel and deep insights into intelligent systems which is particularly relevant to both researchers and students of AI and the cognitive sciences. Seller Inventory # 9783319321110
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Buch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The idea of this book is to establish a new scientific discipline, ¿noology,¿ under which a set of fundamental principles are proposed for the characterization of both naturally occurring and artificial intelligent systems.The methodology adopted in Principles of Noology for the characterization of intelligent systems, or ¿noological systems,¿ is a computational one, much like that of AI. Many AI devices such as predicate logic representations, search mechanisms, heuristics, and computational learning mechanisms are employed but they are recast in a totally new framework for the characterization of noological systems. The computational approach in this book provides a quantitative and high resolution understanding of noological processes, and at the same time the principles and methodologies formulated are directly implementable in AI systems.In contrast to traditional AI that ignores motivational and affective processes, under the paradigm of noology,motivational and affective processes are central to the functioning of noological systems and their roles in noological processes are elucidated in detailed computational terms. In addition, a number of novel representational and learning mechanisms are proposed, and ample examples and computer simulations are provided to show their applications. These include rapid effective causal learning (a novel learning mechanism that allows an AI/noological system to learn causality with a small number of training instances), learning of scripts that enables knowledge chunking and rapid problem solving, and learning of heuristics that further accelerates problem solving. Semantic grounding allows an AI/noological system to ¿truly understand¿ the meaning of the knowledge it encodes. This issue is extensively explored.This is a highly informative book providing novel and deep insights into intelligent systems which is particularly relevant to both researchers and students of AI and the cognitive sciences.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 452 pp. Englisch. Seller Inventory # 9783319321110
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Condition: New. 1st ed. 2016 edition NO-PA16APR2015-KAP. Seller Inventory # 26378437128
Seller: Revaluation Books, Exeter, United Kingdom
Hardcover. Condition: Brand New. 431 pages. 9.20x6.40x1.20 inches. In Stock. Seller Inventory # x-3319321110
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