The Handbook on Reasoning-Based Intelligent Systems

The Handbook on Reasoning-Based Intelligent Systems

Author: Kazumi Nakamatsu

Publisher: World Scientific

Published: 2013

Total Pages: 680

ISBN-13: 9814329487

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This book consists of various contributions in conjunction with the keywords OC reasoningOCO and OC intelligent systemsOCO, which widely covers theoretical to practical aspects of intelligent systems. Therefore, it is suitable for researchers or graduate students who want to study intelligent systems generally."


The Handbook On Reasoning-based Intelligent Systems

The Handbook On Reasoning-based Intelligent Systems

Author: Kazumi Nakamatsu

Publisher: World Scientific

Published: 2013-01-18

Total Pages: 680

ISBN-13: 9814489166

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This book consists of various contributions in conjunction with the keywords “reasoning” and “intelligent systems”, which widely covers theoretical to practical aspects of intelligent systems. Therefore, it is suitable for researchers or graduate students who want to study intelligent systems generally.


Intelligent Systems for Engineers and Scientists

Intelligent Systems for Engineers and Scientists

Author: Adrian A. Hopgood

Publisher: CRC Press

Published: 2012-02-02

Total Pages: 455

ISBN-13: 1466516178

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The third edition of this bestseller examines the principles of artificial intelligence and their application to engineering and science, as well as techniques for developing intelligent systems to solve practical problems. Covering the full spectrum of intelligent systems techniques, it incorporates knowledge-based systems, computational intelligence, and their hybrids. Using clear and concise language, Intelligent Systems for Engineers and Scientists, Third Edition features updates and improvements throughout all chapters. It includes expanded and separated chapters on genetic algorithms and single-candidate optimization techniques, while the chapter on neural networks now covers spiking networks and a range of recurrent networks. The book also provides extended coverage of fuzzy logic, including type-2 and fuzzy control systems. Example programs using rules and uncertainty are presented in an industry-standard format, so that you can run them yourself. The first part of the book describes key techniques of artificial intelligence—including rule-based systems, Bayesian updating, certainty theory, fuzzy logic (types 1 and 2), frames, objects, agents, symbolic learning, case-based reasoning, genetic algorithms, optimization algorithms, neural networks, hybrids, and the Lisp and Prolog languages. The second part describes a wide range of practical applications in interpretation and diagnosis, design and selection, planning, and control. The author provides sufficient detail to help you develop your own intelligent systems for real applications. Whether you are building intelligent systems or you simply want to know more about them, this book provides you with detailed and up-to-date guidance. Check out the significantly expanded set of free web-based resources that support the book at: http://www.adrianhopgood.com/aitoolkit/


Handbook of Temporal Reasoning in Artificial Intelligence

Handbook of Temporal Reasoning in Artificial Intelligence

Author: Michael David Fisher

Publisher: Elsevier

Published: 2005-03-01

Total Pages: 753

ISBN-13: 0080533361

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This collection represents the primary reference work for researchers and students in the area of Temporal Reasoning in Artificial Intelligence. Temporal reasoning has a vital role to play in many areas, particularly Artificial Intelligence. Yet, until now, there has been no single volume collecting together the breadth of work in this area. This collection brings together the leading researchers in a range of relevant areas and provides an coherent description of the breadth of activity concerning temporal reasoning in the filed of Artificial Intelligence.Key Features:- Broad range: foundations; techniques and applications- Leading researchers around the world have written the chapters- Covers many vital applications- Source book for Artificial Intelligence, temporal reasoning- Approaches provide foundation for many future software systems· Broad range: foundations; techniques and applications· Leading researchers around the world have written the chapters· Covers many vital applications· Source book for Artificial Intelligence, temporal reasoning· Approaches provide foundation for many future software systems


Probabilistic Reasoning in Intelligent Systems

Probabilistic Reasoning in Intelligent Systems

Author: Judea Pearl

Publisher: Elsevier

Published: 2014-06-28

Total Pages: 573

ISBN-13: 0080514898

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Probabilistic Reasoning in Intelligent Systems is a complete and accessible account of the theoretical foundations and computational methods that underlie plausible reasoning under uncertainty. The author provides a coherent explication of probability as a language for reasoning with partial belief and offers a unifying perspective on other AI approaches to uncertainty, such as the Dempster-Shafer formalism, truth maintenance systems, and nonmonotonic logic. The author distinguishes syntactic and semantic approaches to uncertainty--and offers techniques, based on belief networks, that provide a mechanism for making semantics-based systems operational. Specifically, network-propagation techniques serve as a mechanism for combining the theoretical coherence of probability theory with modern demands of reasoning-systems technology: modular declarative inputs, conceptually meaningful inferences, and parallel distributed computation. Application areas include diagnosis, forecasting, image interpretation, multi-sensor fusion, decision support systems, plan recognition, planning, speech recognition--in short, almost every task requiring that conclusions be drawn from uncertain clues and incomplete information. Probabilistic Reasoning in Intelligent Systems will be of special interest to scholars and researchers in AI, decision theory, statistics, logic, philosophy, cognitive psychology, and the management sciences. Professionals in the areas of knowledge-based systems, operations research, engineering, and statistics will find theoretical and computational tools of immediate practical use. The book can also be used as an excellent text for graduate-level courses in AI, operations research, or applied probability.


The Handbook of Artificial Intelligence

The Handbook of Artificial Intelligence

Author: Avron Barr

Publisher: Butterworth-Heinemann

Published: 2014-05-12

Total Pages: 443

ISBN-13: 1483214389

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The Handbook of Artificial Intelligence, Volume II focuses on the improvements in artificial intelligence (AI) and its increasing applications, including programming languages, intelligent CAI systems, and the employment of AI in medicine, science, and education. The book first elaborates on programming languages for AI research and applications-oriented AI research. Discussions cover scientific applications, teiresias, applications in chemistry, dependencies and assumptions, AI programming-language features, and LISP. The manuscript then examines applications-oriented AI research in medicine and education, including ICAI systems design, intelligent CAI systems, medical systems, and other applications of AI to education. The manuscript explores automatic programming, as well as the methods of program specification, basic approaches, and automatic programming systems. The book is a valuable source of data for computer science experts and researchers interested in conducting further research in artificial intelligence.


Knowledge Representation and Reasoning

Knowledge Representation and Reasoning

Author: Ronald Brachman

Publisher: Morgan Kaufmann

Published: 2004-05-19

Total Pages: 414

ISBN-13: 1558609326

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Knowledge representation is at the very core of a radical idea for understanding intelligence. This book talks about the central concepts of knowledge representation developed over the years. It is suitable for researchers and practitioners in database management, information retrieval, object-oriented systems and artificial intelligence.


Artificial Intelligence

Artificial Intelligence

Author: Michael Negnevitsky

Publisher: Pearson Education

Published: 2005

Total Pages: 454

ISBN-13: 9780321204660

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Keeping the maths to a minimum, Negnevitsky explains the principles of AI, demonstrates how systems are built, what they are useful for and how to choose the right tool for the job.