Logical Foundations Of Artificial Intelligence

Author: Michael R. Genesereth
Publisher: Morgan Kaufmann
ISBN: 0128015543
Size: 31.91 MB
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Logical Foundations Of Artificial Intelligence from the Author: Michael R. Genesereth. Intended both as a text for advanced undergraduates and graduate students, and as a key reference work for AI researchers and developers, Logical Foundations of Artificial Intelligence is a lucid, rigorous, and comprehensive account of the fundamentals of artificial intelligence from the standpoint of logic. The first section of the book introduces the logicist approach to AI--discussing the representation of declarative knowledge and featuring an introduction to the process of conceptualization, the syntax and semantics of predicate calculus, and the basics of other declarative representations such as frames and semantic nets. This section also provides a simple but powerful inference procedure, resolution, and shows how it can be used in a reasoning system. The next several chapters discuss nonmonotonic reasoning, induction, and reasoning under uncertainty, broadening the logical approach to deal with the inadequacies of strict logical deduction. The third section introduces modal operators that facilitate representing and reasoning about knowledge. This section also develops the process of writing predicate calculus sentences to the metalevel--to permit sentences about sentences and about reasoning processes. The final three chapters discuss the representation of knowledge about states and actions, planning, and intelligent system architecture. End-of-chapter bibliographic and historical comments provide background and point to other works of interest and research. Each chapter also contains numerous student exercises (with solutions provided in an appendix) to reinforce concepts and challenge the learner. A bibliography and index complete this comprehensive work.

Knowledge In Action

Author: Raymond Reiter
Publisher: MIT Press
ISBN: 9780262264310
Size: 12.84 MB
Format: PDF
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Knowledge In Action from the Author: Raymond Reiter. Modeling and implementing dynamical systems is a central problem in artificial intelligence, robotics, software agents, simulation, decision and control theory, and many other disciplines. In recent years, a new approach to representing such systems, grounded in mathematical logic, has been developed within the AI knowledge-representation community.This book presents a comprehensive treatment of these ideas, basing its theoretical and implementation foundations on the situation calculus, a dialect of first-order logic. Within this framework, it develops many features of dynamical systems modeling, including time, processes, concurrency, exogenous events, reactivity, sensing and knowledge, probabilistic uncertainty, and decision theory. It also describes and implements a new family of high-level programming languages suitable for writing control programs for dynamical systems. Finally, it includes situation calculus specifications for a wide range of examples drawn from cognitive robotics, planning, simulation, databases, and decision theory, together with all the implementation code for these examples. This code is available on the book's Web site.

Handbook Of Constraint Programming

Author: Francesca Rossi
Publisher: Elsevier
ISBN: 9780080463803
Size: 42.55 MB
Format: PDF
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Handbook Of Constraint Programming from the Author: Francesca Rossi. Constraint programming is a powerful paradigm for solving combinatorial search problems that draws on a wide range of techniques from artificial intelligence, computer science, databases, programming languages, and operations research. Constraint programming is currently applied with success to many domains, such as scheduling, planning, vehicle routing, configuration, networks, and bioinformatics. The aim of this handbook is to capture the full breadth and depth of the constraint programming field and to be encyclopedic in its scope and coverage. While there are several excellent books on constraint programming, such books necessarily focus on the main notions and techniques and cannot cover also extensions, applications, and languages. The handbook gives a reasonably complete coverage of all these lines of work, based on constraint programming, so that a reader can have a rather precise idea of the whole field and its potential. Of course each line of work is dealt with in a survey-like style, where some details may be neglected in favor of coverage. However, the extensive bibliography of each chapter will help the interested readers to find suitable sources for the missing details. Each chapter of the handbook is intended to be a self-contained survey of a topic, and is written by one or more authors who are leading researchers in the area. The intended audience of the handbook is researchers, graduate students, higher-year undergraduates and practitioners who wish to learn about the state-of-the-art in constraint programming. No prior knowledge about the field is necessary to be able to read the chapters and gather useful knowledge. Researchers from other fields should find in this handbook an effective way to learn about constraint programming and to possibly use some of the constraint programming concepts and techniques in their work, thus providing a means for a fruitful cross-fertilization among different research areas. The handbook is organized in two parts. The first part covers the basic foundations of constraint programming, including the history, the notion of constraint propagation, basic search methods, global constraints, tractability and computational complexity, and important issues in modeling a problem as a constraint problem. The second part covers constraint languages and solver, several useful extensions to the basic framework (such as interval constraints, structured domains, and distributed CSPs), and successful application areas for constraint programming. - Covers the whole field of constraint programming - Survey-style chapters - Five chapters on applications

Multiagent Systems

Author: Yoav Shoham
Publisher: Cambridge University Press
ISBN: 113947524X
Size: 40.45 MB
Format: PDF, ePub
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Multiagent Systems from the Author: Yoav Shoham. Multiagent systems combine multiple autonomous entities, each having diverging interests or different information. This overview of the field offers a computer science perspective, but also draws on ideas from game theory, economics, operations research, logic, philosophy and linguistics. It will serve as a reference for researchers in each of these fields, and be used as a text for advanced undergraduate or graduate courses. The authors emphasize foundations to create a broad and rigorous treatment of their subject, with thorough presentations of distributed problem solving, game theory, multiagent communication and learning, social choice, mechanism design, auctions, cooperative game theory, and modal logics of knowledge and belief. For each topic, basic concepts are introduced, examples are given, proofs of key results are offered, and algorithmic considerations are examined. An appendix covers background material in probability theory, classical logic, Markov decision processes and mathematical programming.

Handbook Of Logic In Artificial Intelligence And Logic Programming Volume 2 Deduction Methodologies

Author: Dov M. Gabbay
Publisher: Oxford University Press
ISBN: 9780198537465
Size: 77.14 MB
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Handbook Of Logic In Artificial Intelligence And Logic Programming Volume 2 Deduction Methodologies from the Author: Dov M. Gabbay. The Handbook of Logic in Artificial Intelligence and Logic Programming is a multi-author volume work covering all major areas of application of logic to AI and logic programming. Initially there will be six volumes containing a total of 43 articles, each article averaging around 75 pages in length but with some rather longer as the subject may demand. The authors are chosen on an international basis and are leaders in the fields covered. The Handbook is a closely co-ordinated work which has been under development for the past five years. Volume 2 covers deduction methodologies.

Subjective Logic

Author: Audun Jøsang
Publisher: Springer
ISBN: 3319423371
Size: 66.82 MB
Format: PDF, ePub, Docs
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Subjective Logic from the Author: Audun Jøsang. This is the first comprehensive treatment of subjective logic and all its operations. The author developed the approach, and in this book he first explains subjective opinions, opinion representation, and decision-making under vagueness and uncertainty, and he then offers a full definition of subjective logic, harmonising the key notations and formalisms, concluding with chapters on trust networks and subjective Bayesian networks, which when combined form general subjective networks. The author shows how real-world situations can be realistically modelled with regard to how situations are perceived, with conclusions that more correctly reflect the ignorance and uncertainties that result from partially uncertain input arguments. The book will help researchers and practitioners to advance, improve and apply subjective logic to build powerful artificial reasoning models and tools for solving real-world problems. A good grounding in discrete mathematics is a prerequisite.

Handbook Of Knowledge Representation

Author: Frank van Harmelen
Publisher: Elsevier
ISBN: 9780080557021
Size: 12.74 MB
Format: PDF, ePub, Mobi
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Handbook Of Knowledge Representation from the Author: Frank van Harmelen. 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

Foundations Of Distributed Artificial Intelligence

Author: G. M. P. O'Hare
Publisher: John Wiley & Sons
ISBN: 9780471006756
Size: 66.78 MB
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Foundations Of Distributed Artificial Intelligence from the Author: G. M. P. O'Hare. This up-to-date collection of contributions from around the globe examines theoretical principles and practical applications, combines a broad view of the field with detailed examinations of specific research topics, and offers superb coverage at both introductory and advanced levels.

Logical Foundations For Cognitive Agents

Author: Hector J. Levesque
Publisher: Springer Science & Business Media
ISBN: 3642602118
Size: 20.48 MB
Format: PDF, ePub
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Logical Foundations For Cognitive Agents from the Author: Hector J. Levesque. It is a pleasure and an honor to be able to present this collection of papers to Ray Reiter on the occasion of his 60th birthday. To say that Ray's research has had a deep impact on the field of Artificial Intel ligence is a considerable understatement. Better to say that anyone thinking of do ing work in areas like deductive databases, default reasoning, diagnosis, reasoning about action, and others should realize that they are likely to end up proving corol laries to Ray's theorems. Sometimes studying related work makes us think harder about the way we approach a problem; studying Ray's work is as likely to make us want to drop our way of doing things and take up his. This is because more than a mere visionary, Ray has always been a true leader. He shows us how to proceed not by pointing from his armchair, but by blazing a trail himself, setting up camp, and waiting for the rest of us to arrive. The International Joint Conference on Ar tificial Intelligence clearly recognized this and awarded Ray its highest honor, the Research Excellence award in 1993, before it had even finished acknowledging all the founders of the field. The papers collected here sample from many of the areas where Ray has done pi oneering work. One of his earliest areas of application was databases, and this is re flected in the chapters by Bertossi et at. and the survey chapter by Minker.

Logics In Ai

Author: David Pearce
Publisher: Springer Science & Business Media
ISBN: 9783540558873
Size: 74.84 MB
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Logics In Ai from the Author: David Pearce. This volume contains the proceedings of JELIA '92, les Journ es Europ ennes sur la Logique en Intelligence Artificielle, or the Third European Workshop on Logics in Artificial Intelligence. The volume contains 2 invited addresses and 21 selected papers covering such topics as: - Logical foundations of logic programming and knowledge-based systems, - Automated theorem proving, - Partial and dynamic logics, - Systems of nonmonotonic reasoning, - Temporal and epistemic logics, - Belief revision. One invited paper, by D. Vakarelov, is on arrow logics, i.e., modal logics for representing graph information. The other, by L.M. Pereira,J.J. Alferes, and J.N. Apar cio, is on default theory for well founded semantics with explicit negation.