Building Large Knowledge-based Systems


Book Description

Chapter one presents the Cyc "philosophy" or paradigm. Chapter 2 presents a global overview of Cyc, including its representation language, the ontology f its knowledge base, and teh environment which it functions. Chapter 3 goes into much more detail on the representation language, including the structure and function of Cyc's metalevel agenda mechanism. Chapter 4 presents heuristics for ontological engineering, the pricnples upon whcihc Cyc's ontology is based. Chapter 5 the provides a glimpse into the global ontology of knowledge. Chapter 6 explains how we "solve" (i.e., adequately handle) the various tough representation thorns (substances, time, space, structures, composite mental/physical objects, beliefs, uncertainty, etc. ). Chapter 7 surveys the mistakes that new knowledge tnereres most often commit. Chapter 8, the concluding chapter, includes a brief status report on the project, and a statement of goals and a timetable for the coming five years.




Knowledge-Based Systems


Book Description

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.




Knowledge-based Systems Analysis and Design


Book Description

An 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.




Towards Very Large Knowledge Bases


Book Description

In the early days of artificial intelligence it was widely believed that powerful computers would, in the future, enable mankind to solve many real-world problems through the use of very general inference procedures and very little domain-specific knowledge. With the benefit of hindsight, this view can now be called quite naive. The field of expert systems, which developed during the early 1970s, embraced the paradigm that Knowledge is Power - even very fast computers require very large amounts of very specific knowledge to solve non-trivial problems. Thus, the field of large knowledge bases has emerged.




Knowledge-based Systems in Artificial Intelligence


Book Description

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, Four-Volume Set


Book Description

The design of knowledge systems is finding myriad applications from corporate databases to general decision support in areas as diverse as engineering, manufacturing and other industrial processes, medicine, business, and economics. In engineering, for example, knowledge bases can be utilized for reliable electric power system operation. In medicine they support complex diagnoses, while in business they inform the process of strategic planning. Programmed securities trading and the defeat of chess champion Kasparov by IBM's Big Blue are two familiar examples of dedicated knowledge bases in combination with an expert system for decision-making.With volumes covering "Implementation," "Optimization," "Computer Techniques," and "Systems and Applications," this comprehensive set constitutes a unique reference source for students, practitioners, and researchers in computer science, engineering, and the broad range of applications areas for knowledge-based systems.




Intelligent Knowledge-Based Systems


Book Description

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.




Handbook of Knowledge Representation


Book Description

Handbook of Knowledge Representation describes the essential foundations of Knowledge Representation, which lies at the core of Artificial Intelligence (AI). The book provides an up-to-date review of twenty-five key topics in knowledge representation, written by the leaders of each field. It includes a tutorial background and cutting-edge developments, as well as applications of Knowledge Representation in a variety of AI systems. This handbook is organized into three parts. Part I deals with general methods in Knowledge Representation and reasoning and covers such topics as classical logic in Knowledge Representation; satisfiability solvers; description logics; constraint programming; conceptual graphs; nonmonotonic reasoning; model-based problem solving; and Bayesian networks. Part II focuses on classes of knowledge and specialized representations, with chapters on temporal representation and reasoning; spatial and physical reasoning; reasoning about knowledge and belief; temporal action logics; and nonmonotonic causal logic. Part III discusses Knowledge Representation in applications such as question answering; the semantic web; automated planning; cognitive robotics; multi-agent systems; and knowledge engineering. This book is an essential resource for graduate students, researchers, and practitioners in knowledge representation and AI. * Make your computer smarter* Handle qualitative and uncertain information* Improve computational tractability to solve your problems easily




Artificial Intelligence


Book Description

Presupposing no familiarity with the technical concepts of either philosophy or computing, this clear introduction reviews the progress made in AI since the inception of the field in 1956. Copeland goes on to analyze what those working in AI must achieve before they can claim to have built a thinking machine and appraises their prospects of succeeding. There are clear introductions to connectionism and to the language of thought hypothesis which weave together material from philosophy, artificial intelligence and neuroscience. John Searle's attacks on AI and cognitive science are countered and close attention is given to foundational issues, including the nature of computation, Turing Machines, the Church-Turing Thesis and the difference between classical symbol processing and parallel distributed processing. The book also explores the possibility of machines having free will and consciousness and concludes with a discussion of in what sense the human brain may be a computer.




XPS-99: Knowledge-Based Systems - Survey and Future Directions


Book Description

A special year like 1999 invites one to draw a balance of what has been achieved in the roughly 30 years of research and development in knowledge based systems (still abbreviated as XPS following the older term “expert systems”) and to take a look at th what the future may hold. For the 5 German conference on knowledge-based systems we therefore asked current and former speakers of the four working groups (FG’s) in the subdivision of knowledge-based systems (FA 1.5) of the German association of Informatics (GI) to present a survey of and future prospects for their respective fields: knowledge engineering, diagnosis, configuration, and case-based reasoning. An additional 14 technical papers deal with current topics in knowledge-based systems with an equal emphasis on methods and applications. They are selected from more than 50 papers accepted in the 4 parallel workshops of XPS-99: a) Knowledge Management, Organizational Memory and Reuse, b) various fields of applications, c) the traditional PuK Workshop (planning and configuration), and d) the GWCBR (German workshop on case-based reasoning). The other papers presented at these workshops are not included in this volume but are available as internal reports of Würzburg university together with the exhibition guide that emphasizing tool support for building knowledge based systems.