Books in Artificial intelligence general

Parallel Processing for Artificial Intelligence 1

1st Edition
Volume 14
June 28, 2014
L.N. Kanal + 3 more
English
eBook
9 7 8 1 4 8 3 2 9 5 7 4 9

Parallel processing for AI problems is of great current interest because of its potential for alleviating the computational demands of AI procedures. The articles in this book consider parallel processing for problems in several areas of artificial intelligence: image processing, knowledge representation in semantic networks, production rules, mechanization of logic, constraint satisfaction, parsing of natural language, data filtering and data mining. The publication is divided into six sections. The first addresses parallel computing for processing and understanding images. The second discusses parallel processing for semantic networks, which are widely used means for representing knowledge - methods which enable efficient and flexible processing of semantic networks are expected to have high utility for building large-scale knowledge-based systems. The third section explores the automatic parallel execution of production systems, which are used extensively in building rule-based expert systems - systems containing large numbers of rules are slow to execute and can significantly benefit from automatic parallel execution. The exploitation of parallelism for the mechanization of logic is dealt with in the fourth section. While sequential control aspects pose problems for the parallelization of production systems, logic has a purely declarative interpretation which does not demand a particular evaluation strategy. In this area, therefore, very large search spaces provide significant potential for parallelism. In particular, this is true for automated theorem proving. The fifth section considers the problem of constraint satisfaction, which is a useful abstraction of a number of important problems in AI and other fields of computer science. It also discusses the technique of consistent labeling as a preprocessing step in the constraint satisfaction problem. Section VI consists of two articles, each on a different, important topic. The first discusses parallel formulation for the Tree Adjoining Grammar (TAG), which is a powerful formalism for describing natural languages. The second examines the suitability of a parallel programming paradigm called Linda, for solving problems in artificial intelligence.Each of the areas discussed in the book holds many open problems, but it is believed that parallel processing will form a key ingredient in achieving at least partial solutions. It is hoped that the contributions, sourced from experts around the world, will inspire readers to take on these challenging areas of inquiry.

Decision Support Systems: Experiences and Expectations

1st Edition
Volume 9
June 28, 2014
T. Jelassi + 2 more
English
eBook
9 7 8 1 4 8 3 2 9 8 4 3 6

This proceedings volume aims to consolidate current knowledge of research into the many fields of DSS, and to identify key issues which should be incorporated into the future research agenda. The main themes of this volume include: DSS for distributed decision processes, Embedding knowledge in DSS, and DSS and organizational change.

Artificial Intelligence in Design '91

1st Edition
May 23, 2014
J. S. Gero
English
eBook
9 7 8 1 4 8 3 1 6 4 8 0 9

Artificial Intelligence in Design '91 is a collection of 47 papers from the First International Conference on Artificial Intelligence in Design held at Edinburgh in June 1991. The papers in this book are grouped into 13 headings, starting with a background of AI design systems and to which extent AI that results from being used as planning tool be applied to quality-oriented design processes in architecture. A constraint-driven approach to object-oriented design is also shown on real-world objects. The use of CADSYN in the structural design of buildings is examined, along with design-dependent knowledge and design-independent knowledge. Discussions on empowering designers with integrated design environments are given whereby design objects may be retrieved from catalogues without requiring users to form queries. Mention is given to automated adjustment of parameter values frequently used in computer routine applications. The book also introduces the Computer Aided Design (CAD) as applied to architecture. Design representation using data models, non-monotonic reasoning in design, and the cognitive aspects of design using empirical studies are discussed. Topics of the industrial applications of AI in design, such as the needed steps to develop a successful AI-based tool, and a review of the Castlemain Project and telecommunication distribution networks follow. This book is suitable for programmers, computer science students, and architects and engineers who use computers in their line of work.

COLT '91

1st Edition
May 23, 2014
COLT
English
eBook
9 7 8 1 4 8 3 2 9 9 1 4 3

COLT '91: Proceedings of the Fourth Annual Workshop on Computational Learning Theory covers the papers presented at the Fourth Workshop on Computational Learning Theory, held at the University of California at Santa Cruz on August 5-7, 1991. The book focuses on quantitative theories of machine learning. The selection first offers information on the role of learning in autonomous robots; tracking drifting concepts using random examples; investigating the distribution assumptions in the PAC learning model; and simultaneous learning of concepts and simultaneous estimation of probabilities.The text then examines the calculation of the learning curve of Bayes optimal classification algorithm for learning a perceptron with noise and a geometric approach to threshold circuit complexity. The manuscript takes a look at learning curves in large neural networks, learnability of infinitary regular sets, and learning monotone DNF with an incomplete membership oracle. Topics include monotone DNF learning algorithm, difficulties in learning infinitary regular sets, learning of a perception rule, and annealed approximation. The book also examines the fast identification of geometric objects with membership queries and a loss bound model for on-line stochastic prediction strategies. The selection is a valuable source of information for researchers interested in the computational learning theory.

Computer-Aided Architectural Design Futures

1st Edition
May 20, 2014
Alan Pipes
English
eBook
9 7 8 1 4 8 3 1 6 2 2 7 0

Computer-Aided Architectural Design Futures contains the proceeding of the International Conference on Computer-Aided Architectural Design, held at Department of Architecture, Technical University of Delft, The Netherlands on September 18-19, 1985. Organized into four parts, the book underlines concepts on computer-aided architectural design. These include systematic design; drawing and visualization; artificial intelligence and knowledge engineering; and implications for practice. This book will be a major reference text for students, researchers, and practitioners.

Knowledge Processing and Applied Artificial Intelligence

1st Edition
May 16, 2014
Soumitra Dutta
English
eBook
9 7 8 1 4 8 3 1 8 3 9 2 3

Knowledge Processing and Applied Artificial Intelligence discusses the business potential of knowledge processing and examines the aspects of applied artificial intelligence technology. The book is comprised of nine chapters that are organized into five parts. The text first covers knowledge processing and applied artificial intelligence, and then proceeds to tackling the techniques for acquiring, representing, and reasoning with knowledge. The next part deals with the process of creating and implementing strategically advantageous knowledge-based system applications. The fourth part covers intelligent interfaces, while the last part details alternative approaches to knowledge processing. The book will be of great use to students and professionals of computer or business related disciplines.

Uncertainty in Artificial Intelligence

1st Edition
May 12, 2014
David Heckerman + 1 more
English
eBook
9 7 8 1 4 8 3 2 1 4 5 1 1

Uncertainty in Artificial Intelligence contains the proceedings of the Ninth Conference on Uncertainty in Artificial Intelligence held at the Catholic University of America in Washington, DC, on July 9-11, 1993. The papers focus on methods of reasoning and decision making under uncertainty as applied to problems in artificial intelligence (AI) and cover topics ranging from knowledge acquisition and automated model construction to learning, planning, temporal reasoning, and machine vision. Comprised of 66 chapters, this book begins with a discussion on causality in Bayesian belief networks before turning to a decision theoretic account of conditional ought statements that rectifies glaring deficiencies in classical deontic logic and forms a sound basis for qualitative decision theory. Subsequent chapters explore trade-offs in constructing and evaluating temporal influence diagrams; normative engineering risk management systems; additive belief-network models; and sensitivity analysis for probability assessments in Bayesian networks. Automated model construction and learning as well as algorithms for inference and decision making are also considered. This monograph will be of interest to both students and practitioners in the fields of AI and computer science.

Relevance Ranking for Vertical Search Engines

1st Edition
January 25, 2014
Bo Long + 1 more
English
Paperback
9 7 8 0 1 2 4 0 7 1 7 1 1
eBook
9 7 8 0 1 2 4 0 7 2 0 2 2

In plain, uncomplicated language, and using detailed examples to explain the key concepts, models, and algorithms in vertical search ranking, Relevance Ranking for Vertical Search Engines teaches readers how to manipulate ranking algorithms to achieve better results in real-world applications. This reference book for professionals covers concepts and theories from the fundamental to the advanced, such as relevance, query intention, location-based relevance ranking, and cross-property ranking. It covers the most recent developments in vertical search ranking applications, such as freshness-based relevance theory for new search applications, location-based relevance theory for local search applications, and cross-property ranking theory for applications involving multiple verticals.

Intelligent Networks

1st Edition
July 3, 2013
Syed V. Ahamed
English
Hardback
9 7 8 0 1 2 4 1 6 6 3 0 1
eBook
9 7 8 0 1 2 4 1 6 6 7 0 7

This textbook offers an insightful study of the intelligent Internet-driven revolutionary and fundamental forces at work in society. Readers will have access to tools and techniques to mentor and monitor these forces rather than be driven by changes in Internet technology and flow of money. These submerged social and human forces form a powerful synergistic foursome web of (a) processor technology, (b) evolving wireless networks of the next generation, (c) the intelligent Internet, and (d) the motivation that drives individuals and corporations. In unison, the technological forces can tear human lives apart for the passive or provide a cohesive set of opportunities for the knowledgeable to lead and reap the rewards in the evolved knowledge society. The book also provides in-depth coverage of the functions embedded in modern processors and intelligent communication networks. It focuses on the convergence of the design of modern processor technologies with the switching and routing methodologies of global intelligent networks. Most of the concepts that are generic to the design of terra-flop parallel processors and the terra-bit fiber-optic networks are presented. This book also highlights recent developments in computer and processor technologies into the microscopic and macroscopic medical functions in hospitals and medical centers.

Swarm Intelligence and Bio-Inspired Computation

1st Edition
May 16, 2013
Xin-She Yang + 4 more
English
Hardback
9 7 8 0 1 2 4 0 5 1 6 3 8
eBook
9 7 8 0 1 2 4 0 5 1 7 7 5

Swarm Intelligence and bio-inspired computation have become increasing popular in the last two decades. Bio-inspired algorithms such as ant colony algorithms, bat algorithms, bee algorithms, firefly algorithms, cuckoo search and particle swarm optimization have been applied in almost every area of science and engineering with a dramatic increase of number of relevant publications. This book reviews the latest developments in swarm intelligence and bio-inspired computation from both the theory and application side, providing a complete resource that analyzes and discusses the latest and future trends in research directions. It can help new researchers to carry out timely research and inspire readers to develop new algorithms. With its impressive breadth and depth, this book will be useful for advanced undergraduate students, PhD students and lecturers in computer science, engineering and science as well as researchers and engineers.

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