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Author: John McDermott
Publisher:
ISBN:
Category : Artificial intelligence
Languages : en
Pages : 628
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Book Description
Author: John McDermott
Publisher:
ISBN:
Category : Artificial intelligence
Languages : en
Pages : 628
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Book Description
Author: International Joint Conferences on Artificial Intelligence
Publisher:
ISBN:
Category : Artificial intelligence
Languages : en
Pages : 612
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Book Description
Author: International Joint Conferences on Artificial Intelligence
Publisher: Morgan Kaufmann
ISBN: 9781558604803
Category : Artificial intelligence
Languages : en
Pages : 1720
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Book Description
Author: International Joint Conference on Artificial Intelligence
Publisher:
ISBN: 9780934613439
Category :
Languages : en
Pages :
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Author: Ronald J. Brachman
Publisher: Morgan Kaufmann Publishers
ISBN:
Category : Computers
Languages : en
Pages : 542
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Book Description
Proceedings held May 1989. Topics include temporal logic, hierarchical knowledge bases, default theories, nonmonotonic and analogical reasoning, formal theories of belief revision, and metareasoning. Annotation copyright Book News, Inc. Portland, Or.
Author: Klaus P. Jantke
Publisher: Springer Science & Business Media
ISBN: 9783540517344
Category : Computers
Languages : en
Pages : 356
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Book Description
In diesem Buch werden die wesentlichen Aspekte der in den letzten Jahren recht kontrovers geführten Diskussion über das Thema Krankheitsverarbeitung diskutiert. Mehrere Beiträge beschäftigen sich theoretisch und empirisch mit der Frage, ob es sinnvoll ist, Coping und Abwehr gegeneinander abzugrenzen. Ein Überblick über Meßverfahren zu Copingprozessen soll die Beurteilung von Ergebnissen erleichtern und bei der Planung und Durchführung von Untersuchungen zu diesem Thema behilflich sein. Empirische Ergebnisse bei verschiedenen Krankheitsbildern (Krebs, Herzinfarkt, chronische Niereninsuffizienz, Multiple Sklerose und Alkoholismus) und unter verschiedenen Fragestellungen demonstrieren Möglichkeiten und Grenzen unterschiedlicher methodischer Vorgehensweisen.
Author: Ipke Wachsmuth
Publisher: Springer Science & Business Media
ISBN: 9783540603436
Category : Computers
Languages : en
Pages : 292
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Book Description
This book constitutes the proceedings of the 19th Annual German Conference on Artificial Intelligence, KI-95, held in Bielefeld in September 1995. The volume opens with full versions of four invited papers devoted to the topic "From Intelligence Models to Intelligent Systems". The main part of the book consists of 17 refereed full papers carefully relected by the program committee; these papers are organized in sections on knowledge organization and optimization, logic and reasoning, nonmonotonicity, action and change, and spatial reasoning.
Author: Daniel S. Weld
Publisher: Morgan Kaufmann
ISBN: 1483214478
Category : Science
Languages : en
Pages : 732
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Book Description
Readings in Qualitative Reasoning about Physical Systems describes the automated reasoning about the physical world using qualitative representations. This text is divided into nine chapters, each focusing on some aspect of qualitative physics. The first chapter deal with qualitative physics, which is concerned with representing and reasoning about the physical world. The goal of qualitative physics is to capture both the commonsense knowledge of the person on the street and the tacit knowledge underlying the quantitative knowledge used by engineers and scientists. The succeeding chapter discusses the qualitative calculus and its role in constructing an envisionment that includes behavior over both mythical time and elapsed time. These topics are followed by reviews of the mathematical aspects of qualitative reasoning, history-based simulation and temporal reasoning, as well as the intelligence in scientific computing. The final chapters are devoted to automated modeling for qualitative reasoning and causal explanations of behavior. These chapters also examine the qualitative kinematics of reasoning about shape and space. This book will prove useful to psychologists and psychiatrists.
Author: Ian Cloete
Publisher: MIT Press
ISBN: 9780262032742
Category : Computers
Languages : en
Pages : 512
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Book Description
Looking at ways to encode prior knowledge and to extract, refine, and revise knowledge within a neurocomputing system.Neurocomputing methods are loosely based on a model of the brain as a network of simple interconnected processing elements corresponding to neurons. These methods derive their power from the collective processing of artificial neurons, the chief advantage being that such systems can learn and adapt to a changing environment. In knowledge-based neurocomputing, the emphasis is on the use and representation of knowledge about an application. Explicit modeling of the knowledge represented by such a system remains a major research topic. The reason is that humans find it difficult to interpret the numeric representation of a neural network.The key assumption of knowledge-based neurocomputing is that knowledge is obtainable from, or can be represented by, a neurocomputing system in a form that humans can understand. That is, the knowledge embedded in the neurocomputing system can also be represented in a symbolic or well-structured form, such as Boolean functions, automata, rules, or other familiar ways. The focus of knowledge-based computing is on methods to encode prior knowledge and to extract, refine, and revise knowledge within a neurocomputing system.ContributorsC. Aldrich, J. Cervenka, I. Cloete, R.A. Cozzio, R. Drossu, J. Fletcher, C.L. Giles, F.S. Gouws, M. Hilario, M. Ishikawa, A. Lozowski, Z. Obradovic, C.W. Omlin, M. Riedmiller, P. Romero, G.P.J. Schmitz, J. Sima, A. Sperduti, M. Spott, J. Weisbrod, J.M. Zurada
Author: Ashwin Ram
Publisher: MIT Press
ISBN: 9780262181655
Category : Computers
Languages : en
Pages : 548
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Book Description
Brings together a diversity of research on goal-driven learning to establish a broad, interdisciplinary framework that describes the goal-driven learning process. In cognitive science, artificial intelligence, psychology, and education, a growing body of research supports the view that the learning process is strongly influenced by the learner's goals. The fundamental tenet of goal-driven learning is that learning is largely an active and strategic process in which the learner, human or machine, attempts to identify and satisfy its information needs in the context of its tasks and goals, its prior knowledge, its capabilities, and environmental opportunities for learning. This book brings together a diversity of research on goal-driven learning to establish a broad, interdisciplinary framework that describes the goal-driven learning process. It collects and solidifies existing results on this important issue in machine and human learning and presents a theoretical framework for future investigations. The book opens with an an overview of goal-driven learning research and computational and cognitive models of the goal-driven learning process. This introduction is followed by a collection of fourteen recent research articles addressing fundamental issues of the field, including psychological and functional arguments for modeling learning as a deliberative, planful process; experimental evaluation of the benefits of utility-based analysis to guide decisions about what to learn; case studies of computational models in which learning is driven by reasoning about learning goals; psychological evidence for human goal-driven learning; and the ramifications of goal-driven learning in educational contexts. The second part of the book presents six position papers reflecting ongoing research and current issues in goal-driven learning. Issues discussed include methods for pursuing psychological studies of goal-driven learning, frameworks for the design of active and multistrategy learning systems, and methods for selecting and balancing the goals that drive learning. A Bradford Book
