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Author: Gheorghe Tecuci
Publisher:
Published: 1995
Total Pages: 344
ISBN-13:
DOWNLOAD EBOOKCurrently, both fields are moving towards an integrated approach using machine learning techniques to automate knowledge acquisition from experts, and knowledge acquisition techniques to guide and assist the learning process.
Author: Rajendra Akerkar
Publisher: Jones & Bartlett Learning
Published: 2010-08-30
Total Pages: 375
ISBN-13: 0763776475
DOWNLOAD EBOOKKnowledge 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.
Author: A. Kidd
Publisher: Springer
Published: 2011-10-12
Total Pages: 208
ISBN-13: 9781461290193
DOWNLOAD EBOOKBuilding an expert system involves eliciting, analyzing, and interpreting the knowledge that a human expert uses when solving problems. Expe rience has shown that this process of "knowledge acquisition" is both difficult and time consuming and is often a major bottleneck in the production of expert systems. Unfortunately, an adequate theoretical basis for knowledge acquisition has not yet been established. This re quires a classification of knowledge domains and problem-solving tasks and an improved understanding of the relationship between knowledge structures in human and machine. In the meantime, expert system builders need access to information about the techniques currently being employed and their effectiveness in different applications. The aim of this book, therefore, is to draw on the experience of AI scientists, cognitive psychologists, and knowledge engineers in discussing particular acquisition techniques and providing practical advice on their application. Each chapter provides a detailed description of a particular technique or methodology applied within a selected task domain. The relative strengths and weaknesses of the tech nique are summarized at the end of each chapter with some suggested guidelines for its use. We hope that this book will not only serve as a practical handbook for expert system builders, but also be of interest to AI and cognitive scientists who are seeking to develop a theory of knowledge acquisition for expert systems.
Author: Bob Wielinga
Publisher: IOS Press
Published: 1990
Total Pages: 390
ISBN-13: 9789051990362
DOWNLOAD EBOOKKnowledge acquisition has become a major area of artificial intelligence and cognitive science research. The papers in this book show that the area of knowledge acquisition for knowledge-based systems is still a diverse field in which a large number of research topics are being addressed. However, several main themes run through the papers. First, the issues of integrating knowledge from different sources and K.A. tools is a salient topic in many papers. A second major topic in the papers is that of knowledge modelling. Research in knowledge-based systems emphasises the use of generic models of reasoning and its underlying knowledge. An important trend in the area of knowledge modelling aims at the formalisation of knowledge models. Where the field of knowledge acquisition was without tools and techniques years ago, now there is a rapidly growing body of techniques and tools. Apart from the integrated workbenches already mentioned above, several papers in this book present new tools. Although knowledge acquisition and machine learning have been considered as separate subfields of AI, there is a tendency for the two fields to come together. This publication combines machine learning techniques with more conventional knowledge elicitation techniques. A framework is presented in which reasoning, problem solving and learning together form a knowledge intensive system that can acquire knowledge from its own experience.
Author: Giner Alor-Hernández
Publisher: Springer
Published: 2017-03-13
Total Pages: 302
ISBN-13: 3319519050
DOWNLOAD EBOOKThis 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.
Author: D. S. W. Tansley
Publisher:
Published: 1993
Total Pages: 552
ISBN-13:
DOWNLOAD EBOOKAn introductory guide to the use of the KADS method in building Knowledge Based Systems. The book includes: introduction to KADS; explanation of KADS Analysis and Design activities and results with use of examples; and libraries of models and other applications.
Author: Cornelius T. Leondes
Publisher: Springer Science & Business Media
Published: 2010-04-28
Total Pages: 2041
ISBN-13: 1402078293
DOWNLOAD EBOOKThis 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.
Author: Ana Landeta Echeberria
Publisher: Springer Nature
Published: 2022-01-22
Total Pages: 210
ISBN-13: 3030882411
DOWNLOAD EBOOKThis 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.
Author: Karen L. McGraw
Publisher:
Published: 1989
Total Pages: 408
ISBN-13:
DOWNLOAD EBOOKThis book presents a practical view of the knowledge acquisition process, its methodologies and techniques, in order to enable readers to develop expert systems knowledge bases more effectively. It strikes a balance between presenting (1) summaries of research in the field of knowledge acquisition and (2) methodologies and techniques that have been applied and tested on numerous programs in various contexts. Written for novice knowledge engineers or others tasked with acquiring knowledge for the systematic development of expert systems. The presentation of the material does not presume a background in either computer science or artificial intelligence.
Author: Clive L. Dym
Publisher: McGraw-Hill Companies
Published: 1991
Total Pages: 440
ISBN-13:
DOWNLOAD EBOOKThis book integrates the fundamentals of artifical intelligence (AI) approaches to knowledge representation with engineering examples. Its unified treatment makes it an essential tool in this emerging new field. Combining an informed approach to AI with engineering problem solving, this book is suitable for an introductory course on AI/expert systems which is specifically offered to engineers. The text provides an in-depth appreciation of the AI fundamentals underlying knowledge-based systems and covers rule-based, frame-based, and object-oriented representation with many engineering illustrations.
