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Author: Peter Jackson
Publisher: Mit Press
ISBN: 9780262100380
Category : Computers
Languages : en
Pages : 255
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Book Description
This book explores the building of expert systems using logic for knowledge representation and meta-level inference for control. It presents research done by members of the expert systems group of the Department of Artificial Intelligence in Edinburgh, often in collaboration with others, based on two hypotheses: that logic is a suitable knowledge representation language, and that an explicit representation of the control regime of the theorem prover has many advantages. The editors introduce these hypotheses and present the arguments in their favor They then describe Socrates' a tool for the construction of expert systems that is based on these assumptions. They devote the remaining chapters to the solution of problems that arise from the restrictions imposed by Socrates's representation language and from the system's inefficiency. The chapters dealing with the representation problem present a reified approach to temporal logic that makes it possible to use nonstandard logics without extending the system, and describe a general proof method for arbitrary modal logics. Those dealing with the efficiency problem discuss the technique of partial evaluation and its limitations, as well as another possible solution known as assertion-time inference. Peter Jackson is a Senior Scientist in the Department of Applied Mathematics and Computer Sciences at the McDonnell Douglas Research Laboratory in St. Louis. Han Reichgelt is a Lecturer in Department of Psychology at the University of Nottingham. Frank van Harmelen is a Research Fellow in the Mathematical Reasoning Group at the University of Edinburgh.
Author: Peter Jackson
Publisher: Mit Press
ISBN: 9780262100380
Category : Computers
Languages : en
Pages : 255
Get Book Here
Book Description
This book explores the building of expert systems using logic for knowledge representation and meta-level inference for control. It presents research done by members of the expert systems group of the Department of Artificial Intelligence in Edinburgh, often in collaboration with others, based on two hypotheses: that logic is a suitable knowledge representation language, and that an explicit representation of the control regime of the theorem prover has many advantages. The editors introduce these hypotheses and present the arguments in their favor They then describe Socrates' a tool for the construction of expert systems that is based on these assumptions. They devote the remaining chapters to the solution of problems that arise from the restrictions imposed by Socrates's representation language and from the system's inefficiency. The chapters dealing with the representation problem present a reified approach to temporal logic that makes it possible to use nonstandard logics without extending the system, and describe a general proof method for arbitrary modal logics. Those dealing with the efficiency problem discuss the technique of partial evaluation and its limitations, as well as another possible solution known as assertion-time inference. Peter Jackson is a Senior Scientist in the Department of Applied Mathematics and Computer Sciences at the McDonnell Douglas Research Laboratory in St. Louis. Han Reichgelt is a Lecturer in Department of Psychology at the University of Nottingham. Frank van Harmelen is a Research Fellow in the Mathematical Reasoning Group at the University of Edinburgh.
Author: Robert C. Moore
Publisher: Center for the Study of Language (CSLI)
ISBN: 9781881526155
Category : Language Arts & Disciplines
Languages : en
Pages : 222
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Book Description
Logic and Representation brings together a collection of essays, written over a period of ten years, that apply formal logic and the notion of explicit representation of knowledge to a variety of problems in artificial intelligence, natural language semantics and the philosophy of mind and language. Particular attention is paid to modelling and reasoning about knowledge and belief, including reasoning about one's own beliefs, and the semantics of sentences about knowledge and belief. Robert C. Moore begins by exploring the role of logic in artificial intelligence, considering logic as an analytical tool, as a basis for reasoning systems, and as a programming language. He then looks at various logical analyses of propositional attitudes, including possible-world models, syntactic models, and models based on Russellian propositions. Next Moore examines autoepistemic logic, a logic for modelling reasoning about one's own beliefs. Rounding out the volume is a section on the semantics of natural language, including a survey of problems in semantic representation; a detailed study of the relations among events, situations, and adverbs; and a presentation of a unification-based approach to semantic interpretation. Robert C. Moore is principal scientist of the Artificial Intelligence Center of SRI International.
Author: Nick Riemer
Publisher: Cambridge University Press
ISBN: 0521851920
Category : Language Arts & Disciplines
Languages : en
Pages : 477
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Book Description
An introduction to the study of meaning in language for undergraduate students.
Author: Ronald Brachman
Publisher: Morgan Kaufmann
ISBN: 1558609326
Category : Computers
Languages : en
Pages : 414
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Book Description
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.
Author: Hector J. Levesque
Publisher: MIT Press
ISBN: 9780262263498
Category : Computers
Languages : en
Pages : 316
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Book Description
This book describes in detail the relationship between symbolic representations of knowledge and abstract states of knowledge, exploring along the way the foundations of knowledge, knowledge bases, knowledge-based systems, and knowledge representation and reasoning. The idea of knowledge bases lies at the heart of symbolic, or "traditional," artificial intelligence. A knowledge-based system decides how to act by running formal reasoning procedures over a body of explicitly represented knowledge—a knowledge base. The system is not programmed for specific tasks; rather, it is told what it needs to know and expected to infer the rest. This book is about the logic of such knowledge bases. It describes in detail the relationship between symbolic representations of knowledge and abstract states of knowledge, exploring along the way the foundations of knowledge, knowledge bases, knowledge-based systems, and knowledge representation and reasoning. Assuming some familiarity with first-order predicate logic, the book offers a new mathematical model of knowledge that is general and expressive yet more workable in practice than previous models. The book presents a style of semantic argument and formal analysis that would be cumbersome or completely impractical with other approaches. It also shows how to treat a knowledge base as an abstract data type, completely specified in an abstract way by the knowledge-level operations defined over it.
Author: Özgür Lütfü Özçep
Publisher: Springer
ISBN: 3030257851
Category : Computers
Languages : en
Pages : 194
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Book Description
Formal specifications are an important tool for the construction, verification and analysis of systems, since without it is hardly possible to explain whether a system worked correctly or showed an expected behavior. This book proposes the use of representation theorems as a means to develop an understanding of all models of a specification in order to exclude possible unintended models, demonstrating the general methodology with representation theorems for applications in qualitative spatial reasoning, data stream processing, and belief revision. For qualitative spatial reasoning, it develops a model of spatial relatedness that captures the scaling context with hierarchical partitions of a spatial domain, and axiomatically characterizes the resulting relations. It also shows that various important properties of stream processing, such as prefix-determinedness or various factorization properties can be axiomatized, and that the axioms are fulfilled by natural classes of stream functions. The third example is belief revision, which is concerned with the revision of knowledge bases under new, potentially incompatible information. In this context, the book considers a subclass of revision operators, namely the class of reinterpretation operators, and characterizes them axiomatically. A characteristic property of reinterpretation operators is that of dissolving potential inconsistencies by reinterpreting symbols of the knowledge base. Intended for researchers in theoretical computer science or one of the above application domains, the book presents results that demonstrate the use of representation theorems for the design and evaluation of formal specifications, and provide the basis for future application-development kits that support application designers with automatically built representations.
Author: John F. Sowa
Publisher:
ISBN: 9787111121497
Category : Knowledge representation (Information theory)
Languages : en
Pages : 594
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Book Description
Author: Frank van Harmelen
Publisher: Elsevier
ISBN: 0080557023
Category : Computers
Languages : en
Pages : 1035
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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
Author: Jack Minker
Publisher: Springer Science & Business Media
ISBN: 9780792372240
Category : Computers
Languages : en
Pages : 640
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Book Description
The use of mathematical logic as a formalism for artificial intelligence was recognized by John McCarthy in 1959 in his paper on Programs with Common Sense. In a series of papers in the 1960's he expanded upon these ideas and continues to do so to this date. It is now 41 years since the idea of using a formal mechanism for AI arose. It is therefore appropriate to consider some of the research, applications and implementations that have resulted from this idea. In early 1995 John McCarthy suggested to me that we have a workshop on Logic-Based Artificial Intelligence (LBAI). In June 1999, the Workshop on Logic-Based Artificial Intelligence was held as a consequence of McCarthy's suggestion. The workshop came about with the support of Ephraim Glinert of the National Science Foundation (IIS-9S2013S), the American Association for Artificial Intelligence who provided support for graduate students to attend, and Joseph JaJa, Director of the University of Maryland Institute for Advanced Computer Studies who provided both manpower and financial support, and the Department of Computer Science. We are grateful for their support. This book consists of refereed papers based on presentations made at the Workshop. Not all of the Workshop participants were able to contribute papers for the book. The common theme of papers at the workshop and in this book is the use of logic as a formalism to solve problems in AI.
Author: Fritz W. Lehmann
Publisher: Pergamon
ISBN:
Category : Computers
Languages : en
Pages : 776
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Book Description
Hardbound. Semantic Networks are graphic structures used to represent concepts and knowledge in computers. Key uses include natural language understanding, information retrieval, machine vision, object-oriented analysis and dynamic control of combat aircraft. This major collection addresses every level of reader interested in the field of knowledge representation. Easy to read surveys of the main research families, most written by the founders, are followed by 25 widely varied articles on semantic networks and the conceptual structure of the world. Some extend ideas of philosopher Charles S Peirce 100 years ahead of his time. Others show connections to databases, lattice theory, semiotics, real-world ontology, graph-grammers, lexicography, relational algebras, property inheritance and semantic primitives. Hundreds of pictures show semantic networks as a visual language of thought.
