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Books in Artificial intelligence expert systems and knowledge based systems

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81-90 of 149 results in All results

Blondie24

  • 1st Edition
  • September 26, 2001
  • David B. Fogel
  • English
  • Paperback
    9 7 8 - 1 - 5 5 8 6 0 - 7 8 3 - 5
  • eBook
    9 7 8 - 0 - 0 8 - 0 5 0 0 1 8 - 8
Blondie24 tells the story of a computer that taught itself to play checkers far better than its creators ever could by using a program that emulated the basic principles of Darwinian evolution--random variation and natural selection-- to discover on its own how to excel at the game. Unlike Deep Blue, the celebrated chess machine that beat Garry Kasparov, the former world champion chess player, this evolutionary program didn't have access to strategies employed by human grand masters, or to databases of moves for the endgame moves, or to other human expertise about the game of chekers. With only the most rudimentary information programmed into its "brain," Blondie24 (the program's Internet username) created its own means of evaluating the complex, changing patterns of pieces that make up a checkers game by evolving artificial neural networks---mathematical models that loosely describe how a brain works.It's fitting that Blondie24 should appear in 2001, the year when we remember Arthur C. Clarke's prediction that one day we would succeed in creating a thinking machine. In this compelling narrative, David Fogel, author and co-creator of Blondie24, describes in convincing detail how evolutionary computation may help to bring us closer to Clarke's vision of HAL. Along the way, he gives readers an inside look into the fascinating history of AI and poses provocative questions about its future.

Intelligent Communication Systems

  • 1st Edition
  • September 24, 2001
  • Nobuyoshi Terashima
  • English
  • Hardback
    9 7 8 - 0 - 1 2 - 6 8 5 3 5 1 - 3
  • eBook
    9 7 8 - 0 - 0 8 - 0 5 1 8 8 6 - 2
This book offers a thorough review of research on intelligent communication systems, focusing on the applications of artificial intelligence to telecommunications that help realize user-friendly interfaces.Intelligent Communication Systems presents the direct result of more than a decade of the author's experiences, research activity, and education in applying artificial intelligence to telecommunications technology. In this book, several fundamental research areas are covered. Some of the areas covered are human-friendly interfaces for telecommunication services with such concepts as Telesensation and HyperReality, computer vision, and the telecommunication description method based on state space. In artificial intelligence research state space is the set of all attainable states of a problem and the possible alternative courses of action to determine the best solution to the problem.

Handbook of Automated Reasoning

  • 1st Edition
  • Volume II
  • June 21, 2001
  • Alan J.A. Robinson + 1 more
  • English
  • Hardback
    9 7 8 - 0 - 4 4 4 - 5 0 8 1 2 - 6

Knowledge-Based Systems, Four-Volume Set

  • 1st Edition
  • July 11, 2000
  • Cornelius T. Leondes
  • English
  • eBook
    9 7 8 - 0 - 0 8 - 0 5 3 5 2 8 - 9
The design of knowledge systems is finding myriad applications from corporate databases to general decision support in areas as diverse as engineering, manufacturing and other industrial processes, medicine, business, and economics. In engineering, for example, knowledge bases can be utilized for reliable electric power system operation. In medicine they support complex diagnoses, while in business they inform the process of strategic planning. Programmed securities trading and the defeat of chess champion Kasparov by IBM's Big Blue are two familiar examples of dedicated knowledge bases in combination with an expert system for decision-making.With volumes covering "Implementation," "Optimization," "Computer Techniques," and "Systems and Applications," this comprehensive set constitutes a unique reference source for students, practitioners, and researchers in computer science, engineering, and the broad range of applications areas for knowledge-based systems.

Quantitative Psychology

  • 1st Edition
  • Volume 15
  • April 1, 2000
  • M. Nowakowska
  • English
  • eBook
    9 7 8 - 0 - 0 8 - 0 8 6 6 6 9 - 7
Examining selected statistical and modeling approaches in psychology, the book concentrates on the topics of mental test theory and theory of measurement. The main objective is not only to present a critical view of the approaches suggested up until now, but also their reinterpretation, extension and enrichment by new theories and concepts, for example, formal theories of semiotics and knowledge, and a unifying theory of actions.The book also shows a relation between test theory and the foundations of fuzzy set theory. It presents new models of measurement tools and new measurement theories of concepts such as objective and subjective time, risk or utility, and discusses the cognitive foundations of these theories, namely the theory of perception and observability.

A Computational Framework for Segmentation and Grouping

  • 1st Edition
  • March 1, 2000
  • G. Medioni + 2 more
  • English
  • eBook
    9 7 8 - 0 - 0 8 - 0 5 2 9 4 8 - 6
This book represents a summary of the research we have been conducting since the early 1990s, and describes a conceptual framework which addresses some current shortcomings, and proposes a unified approach for a broad class of problems. While the framework is defined, our research continues, and some of the elements presented here will no doubt evolve in the coming years.It is organized in eight chapters. In the Introduction chapter, we present the definition of the problems, and give an overview of the proposed approach and its implementation. In particular, we illustrate the limitations of the 2.5D sketch, and motivate the use of a representation in terms of layers instead.In chapter 2, we review some of the relevant research in the literature. The discussion focuses on general computational approaches for early vision, and individual methods are only cited as references. Chapter 3 is the fundamental chapter, as it presents the elements of our salient feature inference engine, and their interaction. It introduced tensors as a way to represent information, tensor fields as a way to encode both constraints and results, and tensor voting as the communication scheme. Chapter 4 describes the feature extraction steps, given the computations performed by the engine described earlier. In chapter 5, we apply the generic framework to the inference of regions, curves, and junctions in 2-D. The input may take the form of 2-D points, with or without orientation. We illustrate the approach on a number of examples, both basic and advanced. In chapter 6, we apply the framework to the inference of surfaces, curves and junctions in 3-D. Here, the input consists of a set of 3-D points, with or without as associated normal or tangent direction. We show a number of illustrative examples, and also point to some applications of the approach. In chapter 7, we use our framework to tackle 3 early vision problems, shape from shading, stereo matching, and optical flow computation. In chapter 8, we conclude this book with a few remarks, and discuss future research directions.We include 3 appendices, one on Tensor Calculus, one dealing with proofs and details of the Feature Extraction process, and one dealing with the companion software packages.

Soft Computing and Intelligent Systems

  • 1st Edition
  • October 15, 1999
  • Madan M. Gupta
  • Naresh K. Sinha
  • English
  • Hardback
    9 7 8 - 0 - 1 2 - 6 4 6 4 9 0 - 0
  • eBook
    9 7 8 - 0 - 0 8 - 0 5 4 1 3 3 - 4
The field of soft computing is emerging from the cutting edge research over the last ten years devoted to fuzzy engineering and genetic algorithms. The subject is being called soft computing and computational intelligence. With acceptance of the research fundamentals in these important areas, the field is expanding into direct applications through engineering and systems science.This book cover the fundamentals of this emerging filed, as well as direct applications and case studies. There is a need for practicing engineers, computer scientists, and system scientists to directly apply "fuzzy" engineering into a wide array of devices and systems.

Applications of Artificial Intelligence

  • 1st Edition
  • Volume 47
  • October 8, 1998
  • Marvin Zelkowitz
  • English
  • eBook
    9 7 8 - 0 - 0 8 - 0 5 6 6 7 9 - 5
Since its first volume in 1960, Advances in Computers has presented detailed coverage of innovations in hardware and software and in computer theory, design, and applications. It has also provided contributors with a medium in which they can examine their subjects in greater depth and breadth than that allowed by standard journal articles. As a result, many articles have become standard references that continue to be of significant, lasting value despite the rapid growth taking place in the field.Volume 47 contains seven chapters. The first four cover artificial intelligence, which is the use of technology to perform tasks generally assumed to require human thinking. These chapters present natural language processing, visualization, and self-replication as machine implementations of human activities. The remaining three chapters cover other recent advances that are important to the information processing field.

Building Intelligent Agents

  • 1st Edition
  • June 12, 1998
  • Gheorghe Tecuci
  • English
  • Paperback
    9 7 8 - 0 - 1 2 - 6 8 5 1 2 5 - 0
Building Intelligent Agents is unique in its comprehensive coverage of the subject. The first part of the book presents an original theory for building intelligent agents and a methodology and tool that implement the theory. The second part of the book presents complex and detailed case studies of building different types of agents: an educational assessment agent, a statistical analysis assessment and support agent, an engineering design assistant, and a virtual military commander. Also featured in this book is Disciple, a toolkit for building interactive agents which function in much the same way as a human apprentice. Disciple-based agents can reason both with incomplete information, but also with information that is potentially incorrect. This approach, in which the agent learns its behavior from its teacher, integrates many machine learning and knowledge acquisition techniques, taking advantage of their complementary strengths to compensate for each others weakness. As a consequence, it significantly reduces (or even eliminates) the involvement of a knowledge engineer in the process of building an intelligent agent.