Books in Artificial intelligence

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

Swarm Intelligence

1st Edition
March 26, 2001
Russell C. Eberhart + 2 more
English
Hardback
9 7 8 1 5 5 8 6 0 5 9 5 4
eBook
9 7 8 0 0 8 0 5 1 8 2 6 8

Traditional methods for creating intelligent computational systems haveprivileged private "internal" cognitive and computational processes. Incontrast, Swarm Intelligence argues that humanintelligence derives from the interactions of individuals in a social worldand further, that this model of intelligence can be effectively applied toartificially intelligent systems. The authors first present the foundations ofthis new approach through an extensive review of the critical literature insocial psychology, cognitive science, and evolutionary computation. Theythen show in detail how these theories and models apply to a newcomputational intelligence methodology—particle swarms—which focuseson adaptation as the key behavior of intelligent systems. Drilling downstill further, the authors describe the practical benefits of applying particleswarm optimization to a range of engineering problems. Developed bythe authors, this algorithm is an extension of cellular automata andprovides a powerful optimization, learning, and problem solving method. This important book presents valuable new insights by exploring theboundaries shared by cognitive science, social psychology, artificial life,artificial intelligence, and evolutionary computation and by applying theseinsights to the solving of difficult engineering problems. Researchers andgraduate students in any of these disciplines will find the materialintriguing, provocative, and revealing as will the curious and savvycomputing professional.

Illustrating Evolutionary Computation with Mathematica

1st Edition
January 29, 2001
Christian Jacob
English
Hardback
9 7 8 1 5 5 8 6 0 6 3 7 1
eBook
9 7 8 0 0 8 0 5 0 8 4 5 0

An essential capacity of intelligence is the ability to learn. An artificially intelligent system that could learn would not have to be programmed for every eventuality; it could adapt to its changing environment and conditions just as biological systems do. Illustrating Evolutionary Computation with Mathematica introduces evolutionary computation to the technically savvy reader who wishes to explore this fascinating and increasingly important field. Unique among books on evolutionary computation, the book also explores the application of evolution to developmental processes in nature, such as the growth processes in cells and plants. If you are a newcomer to the evolutionary computation field, an engineer, a programmer, or even a biologist wanting to learn how to model the evolution and coevolution of plants, this book will provide you with a visually rich and engaging account of this complex subject.

Knowledge-Based Systems, Four-Volume Set

1st Edition
June 20, 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.

Animal Cognition and Behavior

1st Edition
Volume 13
April 1, 2000
R.L. Mellgren
English
eBook
9 7 8 0 0 8 0 8 6 6 6 7 3

Contributed chapters by psychologists and behavioral biologists provide a broad coverage of animal behavior, and governing brain processes. Topics covered include: foraging behavior and strategies, economics and psychology, memory of events and space, time perception, expectancies, food preferences and diet selection, behavior variability and the concept of mind.The volume is designed to satisfy an intderdisciplinary audience, embracing the behavioristic tradition, biological and physiological approaches, and evolutionary theory as philosophical underpinnings to the chapters. Also achieved in this work is a good balance between empirical results and theory.

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 Theory of Cognitive Aging

1st Edition
Volume 28
April 1, 2000
T. Salthouse
English
eBook
9 7 8 0 0 8 0 8 6 6 8 2 6

Over a half-century of research has documented the fact that people of different ages perform at different levels on a variety of tests of cognitive functioning, and yet there are still no comprehensive theories to account for these phenomena. A Theory of Cognitive Aging is intended to begin intellectual discussion in this area by identifying major issues of controversy, and proposing a particular theoretical interpretation based on the notion that the rate of processing information slows down with increased age. Although still quite preliminary, the theoretical perspective is demonstrated to provide a plausible account for age-related differences in functioning on measures of memory, spatial ability and reasoning. The book has four aims: - To advocate a more explicitly theoretical approach to research in the area of cognitive aging. - To outline three important dimensions along which it is argued that any theory of cognitive aging phenomena must take a position. - To evaluate empirical evidence relevant to specific positions along those dimensions. - To summarize the major concepts of the current theory, and to describe its application to selected findings in the research literature.

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.

Kohonen Maps

1st Edition
July 2, 1999
E. Oja + 1 more
English
eBook
9 7 8 0 0 8 0 5 3 5 2 9 6

The Self-Organizing Map, or Kohonen Map, is one of the most widely used neural network algorithms, with thousands of applications covered in the literature. It was one of the strong underlying factors in the popularity of neural networks starting in the early 80's. Currently this method has been included in a large number of commercial and public domain software packages. In this book, top experts on the SOM method take a look at the state of the art and the future of this computing paradigm.The 30 chapters of this book cover the current status of SOM theory, such as connections of SOM to clustering, classification, probabilistic models, and energy functions. Many applications of the SOM are given, with data mining and exploratory data analysis the central topic, applied to large databases of financial data, medical data, free-form text documents, digital images, speech, and process measurements. Biological models related to the SOM are also discussed.

Related subjects

Artificial intelligence expert systems and knowledge based systems

Artificial intelligence general

Cognitive science

Computer human interaction

Evolutionary computation genetic algorithms programming

Fuzzy logic

Machine learning

Natural language and computational linguistics

Neural networks

Planning and scheduling

Reasoning

Robotics and autonomous systems

Life Sciences

Physical Sciences & Engineering

Social Sciences & Humanities

Health