Bücher der Reihe Texts in Computer Science

Logic for Artificial Intelligence and Information Technology is based on student notes used to teach logic to second year undergraduates and Artificial Intelligence to graduate students at the University of London since1984, first at Imperial College and later at King's College.Logic has been applied to a wide variety of subjects such as theoretical computer science, software engineering, hardware design, logic programming, computational linguistics and artificial intelligence. In this way it has served to stimulate the research for clear conceptual foundations.Over the past 20 years many extensions of classical logic such as temporal, modal, relevance, fuzzy, probabilistic and non-monotoinic logics have been widely used in computer science and artificial intelligence, therefore requiring new formulations of classical logic, which can be modified to yield the effect of the new applied logics.The text introduces classical logic in a goal directed way which can easily deviate into discussing other applied logics. It defines the many types of logics and differences between them.Dov Gabbay, FRSC, FAvH, FRSA, FBCS, is Augustus De Morgan Professor of Logic at the University of London. He has written over 300 papers in logic and over 20 books. He is Editor-in-Chief of several leading journals and has published over 50 handbooks of logic volumes. He is a world authority on applied logics and is one of the directors and founder of the UK charity the International Federation of Computational Logic

Automata and Dictionaries is aimed at students and specialists in natural language processing and related disciplines where efficient text analysis plays a role. Large linguistic resources, in particular lexica, are now recognized as a fundamental pre-requisite for all natural language processing tasks. Specialists in this domain cannot afford to be ignorant of the state-of-the-art lexicon-management algorithms. This monograph, which is also intended be used as an advanced text book in computational linguistics, fills a gap in natural language processing monographs and is complementary to other publications in this area.This book is also a source of examples, exercises and problems for software engineering in general. The algorithms that are presented are excellent examples of non-trivial problems of graph construction, graph handling and graph traversal. Even though published in scientific journals, they have not been presented in an easily accessible form so far to teachers and students. These algorithms will also be of interest for the training of software engineers.Chapter 1 of Automata and Dictionaries provides the application-oriented motivation for solving the problems studied in the rest of the book. It introduces and exemplifies several key notions of lexicon-based natural language processing in a way accessible to any computer science student. Chapter 2 surveys the main solutions of the problem, using as an example a very small toy lexicon. Chapter 3 defines the underlying mathematical notions, immediately illustrating theory with practical examples, which makes this part quite readable.Chapters 4 and 5 are dedicated to the two central notions of lexicon construction: the algorithms of determinization and minimization. The standard form of both algorithms is presented, but also their variants and some special cases that occur frequently in practice. The operation of the algorithms is described step by step in examples, introducing the beginner into the world of epsilon-transitions, state heights and reverse automata.Chapter 6 goes a step further into complexity. It is based on algorithms published by scholars from 1998 to now. They are presented here with the same clarity as the preceding, more classical, algorithms. This remarkable achievement owes much to the rigorous structuration of this chapter. These algorithms have variants for transducers, which are presented in Chapter 7 with the same pedagogical skill.The last chapter studies time and space complexity of the algorithms and explains several tricks useful to speed up their operation.

This clearly structured textbook/reference presents a detailed and comprehensive review of the fundamental principles of sequential graph algorithms, approaches for NP-hard graph problems, and approximation algorithms and heuristics for such problems.

This classroom-tested and clearly-written textbook presents a focused guide to the conceptual foundations of compilation, explaining the fundamental principles and algorithms used for defining the syntax of languages, and for implementing simple translators.This significantly updated and expanded third edition has been enhanced with additional coverage of regular expressions, visibly pushdown languages, bottom-up and top-down deterministic parsing algorithms, and new grammar models.Topics and features: describes the principles and methods used in designing syntax-directed applications such as parsing and regular expression matching; covers translations, semantic functions (attribute grammars), and static program analysis by data flow equations; introduces an efficient method for string matching and parsing suitable for ambiguous regular expressions (NEW); presents a focus on extended BNF grammars with their general parser and with LR(1) and LL(1) parsers (NEW); introduces a parallel parsing algorithm that exploits multiple processing threads to speed up syntax analysis of large files; discusses recent formal models of input-driven automata and languages (NEW); includes extensive use of theoretical models of automata, transducers and formal grammars, and describes all algorithms in pseudocode; contains numerous illustrative examples, and supplies a large set of exercises with solutions at an associated website.Advanced undergraduate and graduate students of computer science will find this reader-friendly textbook to be an invaluable guide to the essential concepts of syntax-directed compilation. The fundamental paradigms of language structures are elegantly explained in terms of the underlying theory, without requiring the use of software tools or knowledge of implementation, and through algorithms simple enough to be practiced by paper and pencil.

This practically-oriented textbook introduces the fundamentals of designing digital surveillance systems powered by intelligent computing techniques. describes the essentials of implementing an intelligent surveillance system and analyzing surveillance data, including a range of biometric characteristics;

explains the fundamentals of automata theory, matrices, graph theory, cryptography, coding theory, language theory, and the concepts of computability and decidability;

The book covers the most essential and widely employed material in each area, particularly the material important for real-world applications. Symbolic AI covers areas such as knowledge-based systems, logical reasoning, symbolic machine learning, search techniques, and natural language processing.

In its revised fifth edition, this book covers ethical, social and policy challenges arising from the convergence of computing and telecommunication and the spread of mobile information devices. Asks important questions about the impact of new technologies.

This effective introduction to the key concepts in computational social science includes formal definitions and a glossary, covers topics such as information extraction, social networks and complexity theory, and discusses a range of methodological tools.

There are many kinds of books on formal logic. It does contain a thorough presentation of formal logic and many proof techniques, and as such it contains all the material one would expect to find in a course in formal logic covering completeness but, not incompleteness issues.

This book provides a thorough treatment of image processing with an emphasis on those aspects most used in computer graphics. The authors concentrate on describing and analyzing the underlying concepts rather than on presenting algorithms or pseudocode.

This is an introductory textbook and guide to the rapidly evolving field of predictive text mining. There are chapter summaries, historical and bibliographic remarks, and classroom-tested exercises for each chapter. Descriptive case studies are also included.

This book introduces the fundamental concepts, models, techniques, and results that form the basic paradigms of computing. It examines all the essential topics in formal languages, automata, computability, and complexity.

Introduced forty years ago, relational databases proved unusually succe- ful and durable. As a result, specialized database systems now proliferate trying to capture various pieces of the database market. The information retrieval systems were followed by database systems, which added even more structure to the data and made querying easier.

Using a HDL, Verilog in this case, rather than static circuit diagrams is a big deviation from traditional books on computer architecture.

This book explores one of the most common approaches to program verification, known as the assertional approach. Case studies supplied throughout the book demonstrate the use of the proof systems and formally verify solutions to classical problems.

This book presents current methods for dealing with software reliability, illustrating the advantages and disadvantages of each method. This reference will serve as an introduction to formal methods and techniques and will be a source for learning about various ways to enhance software reliability.