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Logics In Ai
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Download or read book Logics in AI written by Jan van Eijck and published by Springer Science & Business Media. This book was released on 1991-02-26 with total page 580 pages. Available in PDF, EPUB and Kindle. Book excerpt: The European Workshop on Logics in Artificial Intelligence was held at the Centre for Mathematics and Computer Science in Amsterdam, September 10-14, 1990. This volume includes the 29 papers selected and presented at the workshop together with 7 invited papers. The main themes are: - Logic programming and automated theorem proving, - Computational semantics for natural language, - Applications of non-classical logics, - Partial and dynamic logics.
Book Synopsis Logic-Based Artificial Intelligence by : Jack Minker
Download or read book Logic-Based Artificial Intelligence written by Jack Minker and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 600 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Logic for Computer Science and Artificial Intelligence by : Ricardo Caferra
Download or read book Logic for Computer Science and Artificial Intelligence written by Ricardo Caferra and published by John Wiley & Sons. This book was released on 2013-02-04 with total page 378 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Logics in Artificial Intelligence by : Wolfgang Faber
Download or read book Logics in Artificial Intelligence written by Wolfgang Faber and published by Springer Nature. This book was released on 2021-05-12 with total page 462 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 17th European Conference on Logics in Artificial Intelligence, JELIA 2021, held as a virtual event, in May 2021. The 27 full papers and 3 short papers included in this volume were carefully reviewed and selected from 68 submissions. The accepted papers span a number of areas within Logics in AI, including: argumentation; belief revision; reasoning about actions, causality, and change; constraint satisfaction; description logics and ontological reasoning; non-classical logics; and logic programming (answer set programming).
Book Synopsis Logics for Artificial Intelligence by : Raymond Turner
Download or read book Logics for Artificial Intelligence written by Raymond Turner and published by Ellis Horwood. This book was released on 1984 with total page 136 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Handbook of Logic in Artificial Intelligence and Logic Programming: Volume 5: Logic Programming by : Dov M. Gabbay
Download or read book Handbook of Logic in Artificial Intelligence and Logic Programming: Volume 5: Logic Programming written by Dov M. Gabbay and published by Clarendon Press. This book was released on 1998-01-08 with total page 818 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Handbook of Logic in Artificial Intelligence and Logic Programming is a multi-volume work covering all major areas of the application of logic to artificial intelligence and logic programming. The authors are chosen on an international basis and are leaders in the fields covered. Volume 5 is the last in this well-regarded series. Logic is now widely recognized as one of the foundational disciplines of computing. It has found applications in virtually all aspects of the subject, from software and hardware engineering to programming languages and artificial intelligence. In response to the growing need for an in-depth survey of these applications the Handbook of Logic in Artificial Intelligence and its companion, the Handbook of Logic in Computer Science have been created. The Handbooks are a combination of authoritative exposition, comprehensive survey, and fundamental research exploring the underlying themes in the various areas. Some mathematical background is assumed, and much of the material will be of interest to logicians and mathematicians. Volume 5 focuses particularly on logic programming. The chapters, which in many cases are of monograph length and scope, emphasize possible unifying themes.
Book Synopsis Artificial Intelligence and Computing Logic by : Cyrus F. Nourani
Download or read book Artificial Intelligence and Computing Logic written by Cyrus F. Nourani and published by CRC Press. This book was released on 2021-12-23 with total page 273 pages. Available in PDF, EPUB and Kindle. Book excerpt: Focusing on the cutting-edge applications of AI cognitive computing from neuromorphic to quantum cognition as applied to AI business analytics, this new volume explores AI’s importance in managing cognitive processes along with ontological modeling concepts for venturing into new business frontiers. The volume presents a selection of significant new accomplishments in the areas of AI cognitive computing ranging from neurocognition perception and decision-making in the human brain—combining neurocognitive techniques and effective computing—to basic facial recognition computing models. Topics include: Agent neurocomputing techniques for facial expression recognition Computing haptic motion and ontology epistemic Characterizations of morph schemas for visual analytics Learning and perceptive computing Functional and structural neuroimaging modeling Observed links between facial recognition and affective emotional processes Interaction of cognitive and emotional processes during social decision-making Neurocognitive processing of emotional facial expressions in individuals Neurocognitive affective system for emotive robot androids Virtual reality-based affect adaptive neuromorphic computing Executive surveys indicate that cognitive adoption is very important in business strategy for success and to remain competitive. Employing cognitive-based processes provides the way to get the right information in the right hands at the right time, which is the key to winning in the digital era and to driving business value that emphasizes competitive differentiation. Several chapters of the volume address the goal of using cognitive technology to improve search capabilities, to provide personalized customer service in business and in health and wellness, and to create better workflow management. Key features: Looks at the newest frontiers on very popular AI and analytics topics Discusses new techniques for visual analytics and data filtering Shows how AI and cognitive science merges with quantum neurocognitive computing Presents ontology models with ontology preservation data filtering techniques Provides a cross-transposition on AI and digitizations for business model innovations Artificial Intelligence and Computing Logic: Cognitive Technology for AI Business Analytics is a valuable resource that informs businesses and other enterprises the value of artificial intelligence and computing logic applications.
Book Synopsis Logical Foundations of Artificial Intelligence by : Michael R. Genesereth
Download or read book Logical Foundations of Artificial Intelligence written by Michael R. Genesereth and published by Morgan Kaufmann. This book was released on 2012-07-05 with total page 427 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Logics in Artificial Intelligence by : Loizos Michael
Download or read book Logics in Artificial Intelligence written by Loizos Michael and published by Springer. This book was released on 2016-11-02 with total page 586 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 15th European Conference on Logics in Artificial Intelligence, JELIA 2016, held in Larnaca, Cyprus, in November 2015. The 32 full papers and 10 short papers included in this volume were carefully reviewed and selected from 88 submissions. The accepted papers span a number of areas within Logics in AI, including: belief revision, answer set programming, argumentation, probabilistic reasoning, handling inconsistencies, temporal logics and planning, description logics, and decidability and complexity results.
Book Synopsis Logics for Computer and Data Sciences, and Artificial Intelligence by : Lech T. Polkowski
Download or read book Logics for Computer and Data Sciences, and Artificial Intelligence written by Lech T. Polkowski and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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. .
Download or read book Markov Logic written by Pedro Dechter and published by Springer Nature. This book was released on 2022-05-31 with total page 145 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Book Synopsis Epistemic Logic for AI and Computer Science by : John-Jules Ch Meyer
Download or read book Epistemic Logic for AI and Computer Science written by John-Jules Ch Meyer and published by . This book was released on 1995 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Logic for Programming, Artificial Intelligence, and Reasoning by : Ken McMillan
Download or read book Logic for Programming, Artificial Intelligence, and Reasoning written by Ken McMillan and published by Springer. This book was released on 2013-12-05 with total page 806 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 19th International Conference on Logic for Programming, Artificial Intelligence and Reasoning, LPAR-19, held in December 2013 in Stellenbosch, South Africa. The 44 regular papers and 8 tool descriptions and experimental papers included in this volume were carefully reviewed and selected from 152 submissions. The series of International Conferences on Logic for Programming, Artificial Intelligence and Reasoning (LPAR) is a forum where year after year, some of the most renowned researchers in the areas of logic, automated reasoning, computational logic, programming languages and their applications come to present cutting-edge results, to discuss advances in these fields and to exchange ideas in a scientifically emerging part of the world.
Book Synopsis Logic for Programming, Artificial Intelligence, and Reasoning by : Iliano Cervesato
Download or read book Logic for Programming, Artificial Intelligence, and Reasoning written by Iliano Cervesato and published by Springer Science & Business Media. This book was released on 2008-11-13 with total page 727 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 15th International Conference on Logic for Programming, Artificial Intelligence, and Reasoning, LPAR 2008, which took place in Doha, Qatar, during November 22-27, 2008. The 45 revised full papers presented together with 3 invited talks were carefully revised and selected from 153 submissions. The papers address all current issues in automated reasoning, computational logic, programming languages and their applications and are organized in topical sections on automata, linear arithmetic, verification knowledge representation, proof theory, quantified constraints, as well as modal and temporal logics.
Book Synopsis Philosophical Logic and Artificial Intelligence by : Richmond H. Thomason
Download or read book Philosophical Logic and Artificial Intelligence written by Richmond H. Thomason and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 230 pages. Available in PDF, EPUB and Kindle. Book excerpt: cians concerned with using logical tools in philosophy have been keenly aware of the limitations that arise from the original con centration of symbolic logic on the idiom of mathematics, and many of them have worked to create extensions of the received logical theories that would make them more generally applicable in philosophy. Carnap's Testability and Meaning, published in 1936 and 1937, was a good early example of this sort of research, motivated by the inadequacy of first-order formalizations of dis 'This sugar cube is soluble in water'. positional sentences like And in fact there is a continuous history of work on this topic, extending from Carnap's paper to Shoham's contribution to the present volume . . Much of the work in philosophical logic, and much of what has appeared in The Journal of Philosophical Logic, was mo tivated by similar considerations: work in modal logic (includ ing tense, deontic, and epistemic logic), intensional logics, non declaratives, presuppositions, and many other topics. In this sort of research, sin.ce the main point is to devise new formalisms, the technical development tends to be rather shallow in comparison with mathematical logic, though it is sel dom absent: theorems need to be proved in order to justify the formalisms, and sometimes these are nontrivial. On the other hand, much effort has to go into motivating a logical innovation.
Author :Svetlana N. Yanushkevich Publisher :Springer Science & Business Media ISBN 13 :1402020759 Total Pages :333 pages Book Rating :4.4/5 (2 download)
Book Synopsis Artificial Intelligence in Logic Design by : Svetlana N. Yanushkevich
Download or read book Artificial Intelligence in Logic Design written by Svetlana N. Yanushkevich and published by Springer Science & Business Media. This book was released on 2013-03-19 with total page 333 pages. Available in PDF, EPUB and Kindle. Book excerpt: There are three outstanding points of this book. First: for the first time, a collective point of view on the role of artificial intelligence paradigm in logic design is introduced. Second, the book reveals new horizons of logic design tools on the technologies of the near future. Finally, the contributors of the book are twenty recognizable leaders in the field from the seven research centres. The chapters of the book have been carefully reviewed by equally qualified experts. All contributors are experienced in practical electronic design and in teaching engineering courses. Thus, the book's style is accessible to graduate students, practical engineers and researchers.
Book Synopsis Statistical Relational Artificial Intelligence by : Luc De Raedt
Download or read book Statistical Relational Artificial Intelligence written by Luc De Raedt and published by Morgan & Claypool Publishers. This book was released on 2016-03-24 with total page 191 pages. Available in PDF, EPUB and Kindle. Book excerpt: An intelligent agent interacting with the real world will encounter individual people, courses, test results, drugs prescriptions, chairs, boxes, etc., and needs to reason about properties of these individuals and relations among them as well as cope with uncertainty. Uncertainty has been studied in probability theory and graphical models, and relations have been studied in logic, in particular in the predicate calculus and its extensions. This book examines the foundations of combining logic and probability into what are called relational probabilistic models. It introduces representations, inference, and learning techniques for probability, logic, and their combinations. The book focuses on two representations in detail: Markov logic networks, a relational extension of undirected graphical models and weighted first-order predicate calculus formula, and Problog, a probabilistic extension of logic programs that can also be viewed as a Turing-complete relational extension of Bayesian networks.
