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Knowledge-based Systems in Artificial Intelligence

Knowledge-based Systems in Artificial Intelligence
Author: Randall Davis
Publisher:
Total Pages: 522
Release: 1982
Genre: Computers
ISBN:
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AM: discovery in mathematics as heuristic search. Example: discovering prime numbers. Agenda. Heuristics. Concepts. Results. Evaluating AM. Appendixes. Concepts. Heuristics. Trace. Bibliography. Teiresias: applications of meta-level knowledge. Explanation. Knowledge acquisition. Strategies. Conclusions. References.

Knowledge-Based Systems

Knowledge-Based Systems
Author: Rajendra Akerkar
Publisher: Jones & Bartlett Learning
Total Pages: 375
Release: 2010-08-30
Genre: Computers
ISBN: 0763776475
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Knowledge Based Systems (KBS) are systems that use artificial intelligence techniques in the problem solving process. This text is designed to develop an appreciation of KBS and their architecture and to help users understand a broad variety of knowledge based techniques for decision support and planning. It assumes basic computer science skills and a math background that includes set theory, relations, elementary probability, and introductory concepts of artificial intelligence. Each of the 12 chapters are designed to be modular providing instructors with the flexibility to model the book to their own course needs. Exercises are incorporated throughout the text to highlight certain aspects of the material being presented and to stimulate thought and discussion.

Current Trends on Knowledge-Based Systems

Current Trends on Knowledge-Based Systems
Author: Giner Alor-Hernández
Publisher: Springer
Total Pages: 290
Release: 2017-03-13
Genre: Technology & Engineering
ISBN: 3319519050
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This book presents innovative and high-quality research on the implementation of conceptual frameworks, strategies, techniques, methodologies, informatics platforms and models for developing advanced knowledge-based systems and their application in different fields, including Agriculture, Education, Automotive, Electrical Industry, Business Services, Food Manufacturing, Energy Services, Medicine and others. Knowledge-based technologies employ artificial intelligence methods to heuristically address problems that cannot be solved by means of formal techniques. These technologies draw on standard and novel approaches from various disciplines within Computer Science, including Knowledge Engineering, Natural Language Processing, Decision Support Systems, Artificial Intelligence, Databases, Software Engineering, etc. As a combination of different fields of Artificial Intelligence, the area of Knowledge-Based Systems applies knowledge representation, case-based reasoning, neural networks, Semantic Web and TICs used in different domains. The book offers a valuable resource for PhD students, Master’s and undergraduate students of Information Technology (IT)-related degrees such as Computer Science, Information Systems and Electronic Engineering.

Knowledge-based Systems in Artificial Intelligence

Knowledge-based Systems in Artificial Intelligence
Author: Randall Davis
Publisher:
Total Pages: 520
Release: 1982
Genre: Artificial intelligence
ISBN:
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AM: discovery in mathematics as heuristic search. Example: discovering prime numbers. Agenda. Heuristics. Concepts. Results. Evaluating AM. Appendixes. Concepts. Heuristics. Trace. Bibliography. Teiresias: applications of meta-level knowledge. Explanation. Knowledge acquisition. Strategies. Conclusions. References.

The Engineering of Knowledge-based Systems

The Engineering of Knowledge-based Systems
Author: Avelino J. González
Publisher:
Total Pages: 554
Release: 1993
Genre: Computers
ISBN:
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This volume provides comprehensive single-volume coverage of both the theory and the applications of knowledge-based systems.

Knowledge-based Expert Systems in Chemistry

Knowledge-based Expert Systems in Chemistry
Author: Philip Judson
Publisher: Royal Society of Chemistry
Total Pages: 284
Release: 2019-02-07
Genre: Chemistry
ISBN: 1788014715
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There have been significant developments in the use of knowledge-based expert systems in chemistry since the first edition of this book was published in 2009. This new edition has been thoroughly revised and updated to reflect the advances. The underlying theme of the book is still the need for computer systems that work with uncertain or qualitative data to support decision-making based on reasoned judgements. With the continuing evolution of regulations for the assessment of chemical hazards, and changes in thinking about how scientific decisions should be made, that need is ever greater. Knowledge-based expert systems are well established in chemistry, especially in relation to toxicology, and they are used routinely to support regulatory submissions. The effectiveness and continued acceptance of computer prediction depends on our ability to assess the trustworthiness of predictions and the validity of the models on which they are based. Written by a pioneer in the field, this book provides an essential reference for anyone interested in the uses of artificial intelligence for decision making in chemistry. r in the field, this book provides an essential reference for anyone interested in the uses of artificial intelligence for decision making in chemistry.r in the field, this book provides an essential reference for anyone interested in the uses of artificial intelligence for decision making in chemistry.r in the field, this book provides an essential reference for anyone interested in the uses of artificial intelligence for decision making in chemistry.

Uncertainty and Vagueness in Knowledge Based Systems

Uncertainty and Vagueness in Knowledge Based Systems
Author: Rudolf Kruse
Publisher: Springer Science & Business Media
Total Pages: 495
Release: 2012-12-06
Genre: Computers
ISBN: 3642767028
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The primary aim of this monograph is to provide a formal framework for the representation and management of uncertainty and vagueness in the field of artificial intelligence. It puts particular emphasis on a thorough analysis of these phenomena and on the development of sound mathematical modeling approaches. Beyond this theoretical basis the scope of the book includes also implementational aspects and a valuation of existing models and systems. The fundamental ambition of this book is to show that vagueness and un certainty can be handled adequately by using measure-theoretic methods. The presentation of applicable knowledge representation formalisms and reasoning algorithms substantiates the claim that efficiency requirements do not necessar ily require renunciation of an uncompromising mathematical modeling. These results are used to evaluate systems based on probabilistic methods as well as on non-standard concepts such as certainty factors, fuzzy sets or belief functions. The book is intended to be self-contained and addresses researchers and practioneers in the field of knowledge based systems. It is in particular suit able as a textbook for graduate-level students in AI, operations research and applied probability. A solid mathematical background is necessary for reading this book. Essential parts of the material have been the subject of courses given by the first author for students of computer science and mathematics held since 1984 at the University in Braunschweig.

Intelligent Knowledge-Based Systems

Intelligent Knowledge-Based Systems
Author: Cornelius T. Leondes
Publisher: Springer Science & Business Media
Total Pages: 2041
Release: 2010-04-28
Genre: Computers
ISBN: 1402078293
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This five-volume set clearly manifests the great significance of these key technologies for the new economies of the new millennium. The discussions provide a wealth of practical ideas intended to foster innovation in thought and, consequently, in the further development of technology. Together, they comprise a significant and uniquely comprehensive reference source for research workers, practitioners, computer scientists, academics, students, and others on the international scene for years to come.

Artificial Intelligence for Business

Artificial Intelligence for Business
Author: Ana Landeta Echeberria
Publisher: Springer Nature
Total Pages: 210
Release: 2022-01-22
Genre: Business & Economics
ISBN: 3030882411
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This book seeks to build a shared understanding of Artificial Intelligence (AI) within the global business scenario today and in the near future. Drawing on academic theory and real-world case studies, it examines AI’s development and application across a number of business contexts. Taking current scholarship forward in its engagement with AI theory and practice for enterprises and applied research and innovation, it outlines international practices for the promotion of reliable AI systems, trends, research and development, fostering a digital ecosystem for AI and preparing companies for job transformation and building skills. This book will be of great interest to academics studying Digital Business, Digital Strategy, Innovation Management, and Information Technology.

Introduction to Knowledge Systems

Introduction to Knowledge Systems
Author: Mark Stefik
Publisher: Elsevier
Total Pages: 896
Release: 2014-06-28
Genre: Computers
ISBN: 0080509169
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Focusing on fundamental scientific and engineering issues, this book communicates the principles of building and using knowledge systems from the conceptual standpoint as well as the practical. Previous treatments of knowledge systems have focused on applications within a particular field, or on symbol-level representations, such as the use of frame and rule representations. Introduction to Knowledge Systems presents fundamentals of symbol-level representations including representations for time, space, uncertainty, and vagueness. It also compares the knowledge-level organizations for three common knowledge-intensive tasks: classification, configuration, and diagnosis. The art of building knowledge systems incorporates computer science theory, programming practice, and psychology. The scope of this book is appropriately broad, ranging from the design of hierarchical search algorithms to techniques for acquiring the task-specific knowledge needed for successful applications. Each chapter proceeds from concepts to applications, and closes with a brief tour of current research topics and open issues. Readers will come away with a solid foundation that will enable them to create real-world knowledge systems using whatever tools and programming languages are most current and appropriate.