Knowledge Representation and Defeasible Reasoning

Knowledge Representation and Defeasible Reasoning PDF Author: Henry E. Kyburg Jr.
Publisher: Springer Science & Business Media
ISBN: 940090553X
Category : Computers
Languages : en
Pages : 432

Get Book Here

Book Description
This series will include monographs and collections of studies devoted to the investigation and exploration of knowledge, information, and data processing systems of all kinds, no matter whether human, (other) ani mal, or machine. Its scope is intended to span the full range of interests from classical problems in the philosophy of mind and philosophical psy chology through issues in cognitive psychology and sociobiology (concerning the mental capabilities of other species) to ideas related to artificial intelli gence and computer science. While primary emphasis will be placed upon theoretical, conceptual, and epistemological aspects of these problems and domains, empirical, experimental, and methodological studies will also ap pear from time to time. The present volume provides a collection of studies that focus on some of the central problems within the domain of artificial intelligence. These difficulties fall into four principal areas: defeasible reasoning (including the frame problem as apart), ordinary language (and the representation prob lems that it generates), the revision of beliefs (and its rules of inference), and knowledge representation (and the logical problems that are encountered there). These papers make original contributions to each of these areas of inquiry and should be of special interest to those who understand the crucial role that is played by questions of logical form. They vividly illustrate the benefits that can emerge from collaborative efforts involving scholars from linguistics, philosophy, computer science, and AI. J. H. F.

Knowledge Representation and Defeasible Reasoning

Knowledge Representation and Defeasible Reasoning PDF Author: Henry E. Kyburg Jr.
Publisher: Springer Science & Business Media
ISBN: 940090553X
Category : Computers
Languages : en
Pages : 432

Get Book Here

Book Description
This series will include monographs and collections of studies devoted to the investigation and exploration of knowledge, information, and data processing systems of all kinds, no matter whether human, (other) ani mal, or machine. Its scope is intended to span the full range of interests from classical problems in the philosophy of mind and philosophical psy chology through issues in cognitive psychology and sociobiology (concerning the mental capabilities of other species) to ideas related to artificial intelli gence and computer science. While primary emphasis will be placed upon theoretical, conceptual, and epistemological aspects of these problems and domains, empirical, experimental, and methodological studies will also ap pear from time to time. The present volume provides a collection of studies that focus on some of the central problems within the domain of artificial intelligence. These difficulties fall into four principal areas: defeasible reasoning (including the frame problem as apart), ordinary language (and the representation prob lems that it generates), the revision of beliefs (and its rules of inference), and knowledge representation (and the logical problems that are encountered there). These papers make original contributions to each of these areas of inquiry and should be of special interest to those who understand the crucial role that is played by questions of logical form. They vividly illustrate the benefits that can emerge from collaborative efforts involving scholars from linguistics, philosophy, computer science, and AI. J. H. F.

Knowledge Representation, Reasoning, and the Design of Intelligent Agents

Knowledge Representation, Reasoning, and the Design of Intelligent Agents PDF Author: Michael Gelfond
Publisher: Cambridge University Press
ISBN: 1107782872
Category : Computers
Languages : en
Pages : 363

Get Book Here

Book Description
Knowledge representation and reasoning is the foundation of artificial intelligence, declarative programming, and the design of knowledge-intensive software systems capable of performing intelligent tasks. Using logical and probabilistic formalisms based on answer set programming (ASP) and action languages, this book shows how knowledge-intensive systems can be given knowledge about the world and how it can be used to solve non-trivial computational problems. The authors maintain a balance between mathematical analysis and practical design of intelligent agents. All the concepts, such as answering queries, planning, diagnostics, and probabilistic reasoning, are illustrated by programs of ASP. The text can be used for AI-related undergraduate and graduate classes and by researchers who would like to learn more about ASP and knowledge representation.

Knowledge Representation and Reasoning Under Uncertainty

Knowledge Representation and Reasoning Under Uncertainty PDF Author: Michael Masuch
Publisher: Springer Science & Business Media
ISBN: 9783540580959
Category : Computers
Languages : en
Pages : 252

Get Book Here

Book Description
This volume is based on the International Conference Logic at Work, held in Amsterdam, The Netherlands, in December 1992. The 14 papers in this volume are selected from 86 submissions and 8 invited contributions and are all devoted to knowledge representation and reasoning under uncertainty, which are core issues of formal artificial intelligence. Nowadays, logic is not any longer mainly associated to mathematical and philosophical problems. The term applied logic has a far wider meaning, as numerous applications of logical methods, particularly in computer science, artificial intelligence, or formal linguistics, testify. As demonstrated also in this volume, a variety of non-standard logics gained increased importance for knowledge representation and reasoning under uncertainty.

Defeasible Deontic Logic

Defeasible Deontic Logic PDF Author: Donald Nute
Publisher: Springer Science & Business Media
ISBN: 9780792346302
Category : Philosophy
Languages : en
Pages : 376

Get Book Here

Book Description
These 13 papers collected from several meetings of the Society for Exact Philosophy from 1993-96 take a variety of approaches to the task of integrating normative and defeasible reasoning. While most of the papers propose some version of defeasible deontic logic, a few consider alternatives approaches to solving some of the puzzles of normative reasoning that deontic reasoning has failed to resolve. The authors also describe standard deontic logic. Name index only. Annotation copyrighted by Book News, Inc., Portland, OR

Knowledge Representation and Reasoning

Knowledge Representation and Reasoning PDF Author: Ronald Brachman
Publisher: Morgan Kaufmann
ISBN: 1558609326
Category : Computers
Languages : en
Pages : 414

Get Book Here

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.

Deontic Logic in Computer Science

Deontic Logic in Computer Science PDF Author: John-Jules Ch. Meyer
Publisher:
ISBN:
Category : Computers
Languages : en
Pages : 344

Get Book Here

Book Description
A useful logic in which to specify normative system behaviour, deontic logic has a broad spectrum of possible applications within the field: from legal expert systems to natural language processing, database integrity to electronic contracting and the specification of fault-tolerant software.

Representing and Reasoning with Probabilistic Knowledge

Representing and Reasoning with Probabilistic Knowledge PDF Author: Fahiem Bacchus
Publisher: Cambridge, Mass. : MIT Press
ISBN:
Category : Computers
Languages : en
Pages : 264

Get Book Here

Book Description
Probabilistic information has many uses in an intelligent system. This book explores logical formalisms for representing and reasoning with probabilistic information that will be of particular value to researchers in nonmonotonic reasoning, applications of probabilities, and knowledge representation. It demonstrates that probabilities are not limited to particular applications, like expert systems; they have an important role to play in the formal design and specification of intelligent systems in general. Fahiem Bacchus focuses on two distinct notions of probabilities: one propositional, involving degrees of belief, the other proportional, involving statistics. He constructs distinct logics with different semantics for each type of probability that are a significant advance in the formal tools available for representing and reasoning with probabilities. These logics can represent an extensive variety of qualitative assertions, eliminating requirements for exact point-valued probabilities, and they can represent firstshy;order logical information. The logics also have proof theories which give a formal specification for a class of reasoning that subsumes and integrates most of the probabilistic reasoning schemes so far developed in AI. Using the new logical tools to connect statistical with propositional probability, Bacchus also proposes a system of direct inference in which degrees of belief can be inferred from statistical knowledge and demonstrates how this mechanism can be applied to yield a powerful and intuitively satisfying system of defeasible or default reasoning. Fahiem Bacchus is Assistant Professor of Computer Science at the University of Waterloo, Ontario. Contents: Introduction. Propositional Probabilities. Statistical Probabilities. Combining Statistical and Propositional Probabilities Default Inferences from Statistical Knowledge.

Legal Knowledge and Information Systems

Legal Knowledge and Information Systems PDF Author: M. Araszkiewicz
Publisher: IOS Press
ISBN: 1643680498
Category : Computers
Languages : en
Pages : 274

Get Book Here

Book Description
In recent years, the application of machine learning tools to legally relevant tasks has become much more prevalent, and the growing influence of AI in the legal sphere has prompted the profession to take more of an interest in the explainability, trustworthiness, and responsibility of intelligent systems. This book presents the proceedings of the 32nd International Conference on Legal Knowledge and Information Systems (JURIX 2019), held in Madrid, Spain, from 11 to 13 December 2019. Traditionally focused on legal knowledge representation and engineering, computational models of legal reasoning, and analyses of legal data, more recently the conference has also encompassed the use of machine learning tools. A total of 81 submissions were received for the conference, of which 14 were selected as full papers and 17 as short papers. A further 3 submissions were accepted as demo presentations, resulting in a total acceptance rate of 41.98%, with a competitive 25.5% acceptance rate for full papers. The 34 papers presented here cover a broad range of topics, from computational models of legal argumentation, case-based reasoning, legal ontologies, and evidential reasoning, through classification of different types of text in legal documents and comparing similarities, to the relevance of judicial decisions to issues of governmental transparency. The book will be of interest to all those whose work involves the use of knowledge and information systems in the legal sphere.

A Logical Theory of Nonmonotonic Inference and Belief Change

A Logical Theory of Nonmonotonic Inference and Belief Change PDF Author: Alexander Bochman
Publisher: Springer Science & Business Media
ISBN: 9783540417668
Category : Computers
Languages : en
Pages : 456

Get Book Here

Book Description
This is the first book that integrates nonmonotonic reasoning and belief change into a single framework from an artificial intelligence logic point-of-view. The approach to both these subjects is based on a powerful notion of an epistemic state that subsumes both existing models for nonmonotonic inference and current models for belief change. Many results and constructions in the book are completely new and have not appeared earlier in the literature.

Reasoning About Knowledge

Reasoning About Knowledge PDF Author: Ronald Fagin
Publisher: MIT Press
ISBN: 9780262562003
Category : Business & Economics
Languages : en
Pages : 576

Get Book Here

Book Description
Reasoning about knowledge—particularly the knowledge of agents who reason about the world and each other's knowledge—was once the exclusive province of philosophers and puzzle solvers. More recently, this type of reasoning has been shown to play a key role in a surprising number of contexts, from understanding conversations to the analysis of distributed computer algorithms. Reasoning About Knowledge is the first book to provide a general discussion of approaches to reasoning about knowledge and its applications to distributed systems, artificial intelligence, and game theory. It brings eight years of work by the authors into a cohesive framework for understanding and analyzing reasoning about knowledge that is intuitive, mathematically well founded, useful in practice, and widely applicable. The book is almost completely self-contained and should be accessible to readers in a variety of disciplines, including computer science, artificial intelligence, linguistics, philosophy, cognitive science, and game theory. Each chapter includes exercises and bibliographic notes.