Logic for Programming, Artificial Intelligence, and Reasoning
Logic for Programming, Artificial Intelligence, and Reasoning

Author: Ken McMillan

Publisher: Springer

Published: 2013-12-05

Total Pages: 806

ISBN-13: 3642452213

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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.

Logic for Programming, Artificial Intelligence, and Reasoning
Logic for Programming, Artificial Intelligence, and Reasoning

Author: Matthias Baaz

Publisher: Springer

Published: 2003-06-30

Total Pages: 476

ISBN-13: 3540360786

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This book constitutes the refereed proceedings of the 9th International Conference on Logic for Programming, Artificial Intelligence, and Reasoning, LPAR 2002, held in Tbilisi, Georgia in October 2002.The 30 revised full papers presented were carefully reviewed and selected from 68 submissions. Among the topics covered are constraint programming, formal software enginering, formal verification, resolution, unification, proof planning, agent splitting, binary decision diagrams, binding, linear logic, Isabelle theorem prover, guided reduction, etc.

Inductive Logic Programming
Inductive Logic Programming

Author: Francesco Bergadano

Publisher: MIT Press

Published: 1996

Total Pages: 264

ISBN-13: 9780262023931

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Although Inductive Logic Programming (ILP) is generally thought of as a research area at the intersection of machine learning and computational logic, Bergadano and Gunetti propose that most of the research in ILP has in fact come from machine learning, particularly in the evolution of inductive reasoning from pattern recognition, through initial approaches to symbolic machine learning, to recent techniques for learning relational concepts. In this book they provide an extended, up-to-date survey of ILP, emphasizing methods and systems suitable for software engineering applications, including inductive program development, testing, and maintenance. Inductive Logic Programming includes a definition of the basic ILP problem and its variations (incremental, with queries, for multiple predicates and predicate invention capabilities), a description of bottom-up operators and techniques (such as least general generalization, inverse resolution, and inverse implication), an analysis of top-down methods (mainly MIS and FOIL-like systems), and a survey of methods and languages for specifying inductive bias. Logic Programming series

Logical Foundations of Artificial Intelligence
Logical Foundations of Artificial Intelligence

Author: Michael R. Genesereth

Publisher: Morgan Kaufmann

Published: 2012-07-05

Total Pages: 427

ISBN-13: 0128015543

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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.

Simply Logical
Simply Logical

Author: Peter Flach

Publisher: Wiley

Published: 1994-04-07

Total Pages: 256

ISBN-13: 9780471942153

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An introduction to Prolog programming for artificial intelligence covering both basic and advanced AI material. A unique advantage to this work is the combination of AI, Prolog and Logic. Each technique is accompanied by a program implementing it. Seeks to simplify the basic concepts of logic programming. Contains exercises and authentic examples to help facilitate the understanding of difficult concepts.

Logic Programming and Non-Monotonic Reasoning
Logic Programming and Non-Monotonic Reasoning

Author: Lua-S Moniz Pereira

Publisher: MIT Press

Published: 1993

Total Pages: 518

ISBN-13: 9780262660839

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This is the second in a series of workshops that are bringing together researchers from the theoretical end of both the logic programming and artificial intelligence communities to discuss their mutual interests. This workshop emphasizes the relationship between logic programming and non-monotonic reasoning.Luis' Moniz Pereira is Professor in the Department of Computer Science at the Universidade Nova Lisboa, Portugal. Anil Nerode is Professor and Director of the Mathematical Sciences Institute at Cornell University.Topics include: Stable Semantics. Autoepistemic Logic. Abduction. Implementation Issues. Well-founded Semantics. Truth Maintenance. Probabilistic Theories. Applications. Default Logic. Diagnosis. Complexity and Theory. Handling Inconsistency.

Logic-Based Artificial Intelligence
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.

Handbook of Logic in Artificial Intelligence and Logic Programming: Volume 5: Logic Programming
Handbook of Logic in Artificial Intelligence and Logic Programming: Volume 5: Logic Programming

Author: Dov M. Gabbay

Publisher: Clarendon Press

Published: 1998-01-08

Total Pages: 818

ISBN-13: 0191546283

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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.

Probabilistic Inductive Logic Programming
Probabilistic Inductive Logic Programming

Author: Luc De Raedt

Publisher: Springer

Published: 2008-02-26

Total Pages: 348

ISBN-13: 354078652X

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This book provides an introduction to probabilistic inductive logic programming. It places emphasis on the methods based on logic programming principles and covers formalisms and systems, implementations and applications, as well as theory.

Mathematical Aspects of Logic Programming Semantics
Mathematical Aspects of Logic Programming Semantics

Author: Pascal Hitzler

Publisher: CRC Press

Published: 2016-04-19

Total Pages: 307

ISBN-13: 1000218724

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Covering the authors' own state-of-the-art research results, this book presents a rigorous, modern account of the mathematical methods and tools required for the semantic analysis of logic programs. It significantly extends the tools and methods from traditional order theory to include nonconventional methods from mathematical analysis that depend on topology, domain theory, generalized distance functions, and associated fixed-point theory. The authors closely examine the interrelationships between various semantics as well as the integration of logic programming and connectionist systems/neural networks.