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Logics for Computer and Data Sciences, and Artificial Intelligence

Author: Lech T. Polkowski

Publisher: Springer Nature

Published: 2022-01-01

Total Pages: 372

ISBN-13: 3030916804

This volume offers the reader a systematic and throughout account of branches of logic instrumental for computer science, data science and artificial intelligence. Addressed in it are propositional, predicate, modal, epistemic, dynamic, temporal logics as well as applicable in data science many-valued logics and logics of concepts (rough logics). It offers a look into second-order logics and approximate logics of parts. The book concludes with appendices on set theory, algebraic structures, computability, complexity, MV-algebras and transition systems, automata and formal grammars. By this composition of the text, the reader obtains a self-contained exposition that can serve as the textbook on logics and relevant disciplines as well as a reference text.

Logic: Reference Book for Computer Scientists

Author: Lech T. Polkowski

Publisher: Springer Nature

Published: 2023-11-04

Total Pages: 489

ISBN-13: 3031420349

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The book gives all interested in computer science, a deep review of relevant aspects of logic. In its scope are classical and non-classical logics. The content will be valid as well for those interested in linguistic, philosophy and many other areas of research both in humane and technical branches of science as logic permeates all genuine realms of science. The book contains a substantial part of classical results in logic like those by Gödel, Tarski, Church and Rosser as well as later developments like many-valued logics, logics for knowledge engineering, first-order logics plus inductive definitions. The exposition is rigorous yet without unnecessary abstractionism, so it should be accessible to readers from many disciplines of science. Each chapter contains a problem section, and problems are borrowed from research publications which allows for passing additional information, and it allows readers to test their skills. Extensive bibliography of 270 positions directs readers to research works of importance.

Logics for Computer Science

Author: Anita Wasilewska

Publisher: Springer

Published: 2018-11-03

Total Pages: 535

ISBN-13: 3319925911

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Providing an in-depth introduction to fundamental classical and non-classical logics, this textbook offers a comprehensive survey of logics for computer scientists. Logics for Computer Science contains intuitive introductory chapters explaining the need for logical investigations, motivations for different types of logics and some of their history. They are followed by strict formal approach chapters. All chapters contain many detailed examples explaining each of the introduced notions and definitions, well chosen sets of exercises with carefully written solutions, and sets of homework. While many logic books are available, they were written by logicians for logicians, not for computer scientists. They usually choose one particular way of presenting the material and use a specialized language. Logics for Computer Science discusses Gentzen as well as Hilbert formalizations, first order theories, the Hilbert Program, Godel's first and second incompleteness theorems and their proofs. It also introduces and discusses some many valued logics, modal logics and introduces algebraic models for classical, intuitionistic, and modal S4 and S5 logics. The theory of computation is based on concepts defined by logicians and mathematicians. Logic plays a fundamental role in computer science, and this book explains the basic theorems, as well as different techniques of proving them in classical and some non-classical logics. Important applications derived from concepts of logic for computer technology include Artificial Intelligence and Software Engineering. In addition to Computer Science, this book may also find an audience in mathematics and philosophy courses, and some of the chapters are also useful for a course in Artificial Intelligence.

Logic for Computer Science and Artificial Intelligence

Author: Ricardo Caferra

Publisher: John Wiley & Sons

Published: 2013-02-04

Total Pages: 378

ISBN-13: 1118604261

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Logic and its components (propositional, first-order, non-classical) play a key role in Computer Science and Artificial Intelligence. While a large amount of information exists scattered throughout various media (books, journal articles, webpages, etc.), the diffuse nature of these sources is problematic and logic as a topic benefits from a unified approach. Logic for Computer Science and Artificial Intelligence utilizes this format, surveying the tableaux, resolution, Davis and Putnam methods, logic programming, as well as for example unification and subsumption. For non-classical logics, the translation method is detailed. Logic for Computer Science and Artificial Intelligence is the classroom-tested result of several years of teaching at Grenoble INP (Ensimag). It is conceived to allow self-instruction for a beginner with basic knowledge in Mathematics and Computer Science, but is also highly suitable for use in traditional courses. The reader is guided by clearly motivated concepts, introductions, historical remarks, side notes concerning connections with other disciplines, and numerous exercises, complete with detailed solutions, The title provides the reader with the tools needed to arrive naturally at practical implementations of the concepts and techniques discussed, allowing for the design of algorithms to solve problems.

Logic for Computer Scientists

Author: Uwe Schöning

Publisher: Springer Science & Business Media

Published: 2009-11-03

Total Pages: 173

ISBN-13: 0817647635

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This book introduces the notions and methods of formal logic from a computer science standpoint, covering propositional logic, predicate logic, and foundations of logic programming. The classic text is replete with illustrative examples and exercises. It presents applications and themes of computer science research such as resolution, automated deduction, and logic programming in a rigorous but readable way. The style and scope of the work, rounded out by the inclusion of exercises, make this an excellent textbook for an advanced undergraduate course in logic for computer scientists.

Markov Logic

Author: Pedro Dechter

Publisher: Springer Nature

Published: 2022-05-31

Total Pages: 145

ISBN-13: 3031015495

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Most subfields of computer science have an interface layer via which applications communicate with the infrastructure, and this is key to their success (e.g., the Internet in networking, the relational model in databases, etc.). So far this interface layer has been missing in AI. First-order logic and probabilistic graphical models each have some of the necessary features, but a viable interface layer requires combining both. Markov logic is a powerful new language that accomplishes this by attaching weights to first-order formulas and treating them as templates for features of Markov random fields. Most statistical models in wide use are special cases of Markov logic, and first-order logic is its infinite-weight limit. Inference algorithms for Markov logic combine ideas from satisfiability, Markov chain Monte Carlo, belief propagation, and resolution. Learning algorithms make use of conditional likelihood, convex optimization, and inductive logic programming. Markov logic has been successfully applied to problems in information extraction and integration, natural language processing, robot mapping, social networks, computational biology, and others, and is the basis of the open-source Alchemy system. Table of Contents: Introduction / Markov Logic / Inference / Learning / Extensions / Applications / Conclusion

Logic-Based Artificial Intelligence

Author: Jack Minker

Publisher: Springer Science & Business Media

Published: 2000-12-31

Total Pages: 640

ISBN-13: 9780792372240

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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.

Temporal Logics in Computer Science

Author: Stéphane Demri

Publisher: Cambridge University Press

Published: 2016-10-13

Total Pages: 753

ISBN-13: 1107028361

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A comprehensive, modern and technically precise exposition of the theory and main applications of temporal logics in computer science.

Epistemic Logic for AI and Computer Science

Author: John-Jules Ch Meyer

Publisher:

Published: 1995

Total Pages: 354

ISBN-13: 9780521460149

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Epistemic logic has grown from its philosophical beginnings to find diverse applications in computer science, and as a means of reasoning about the knowledge and belief of agents. This book provides a broad introduction to the subject, along with many exercises and their solutions. The authors begin by presenting the necessary apparatus from mathematics and logic, including Kripke semantics and the well-known modal logics K, T, S4 and S5. Then they turn to applications in the context of distributed systems and artificial intelligence. These include the notions of common knowledge, distributed knowledge, explicit and implicit belief, the interplays between knowledge and time, and knowledge and action, as well as a graded (or numerical) variant of the epistemic operators. The authors also discuss extensively the problem of logical omniscience. They cover Halpern & Moses' theory of honest formulas, and they make a digression into the realm of nonmonotonic reasoning and preferential entailment. They discuss Moore's autoepistemic logic, together with Levesque's related logic of "all I know". Furthermore, they show how one can base default and counterfactual reasoning on epistemic logic. Graduate students in philosophy or in computer science, especially those with an interest in AI, will find this book useful.

Logics for Artificial Intelligence

Author: Raymond Turner

Publisher: Ellis Horwood

Published: 1984

Total Pages: 136

ISBN-13:

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In Logics for Artificial Intelligence, Raymond Turner leads us on a whirl-wind tour of nonstandard logics and their general applications to Al and computer science.