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The latest scientific findings indicate that emotions play an essential role in decision making, perception, learning, and more -- that is, they influence the very mechanisms of rational thinking. According to Rosalind Picard, if we want computers to be genuinely intelligent and to interact naturally with us, we must give computers the ability to recognize, understand, even to have and express emotions. Part 1 of this book provides the intellectual framework for affective computing. It includes background on human emotions, requirements for emotionally intelligent computers, applications of affective computing, and moral and social questions raised by the technology. Part 2 discusses the design and construction of affective computers. Topics in Part 2 include signal-based representations of emotions, human affect recognition as a pattern recognition and learning problem, recent and ongoing efforts to build models of emotion for synthesizing emotions in computers, and the new application area of affective wearable computers.

This comprehensive collection of twenty-nine readings covers artificial intelligence from its historical roots to current research directions and practice. With its helpful critique of the selections, extensive bibliography, and clear presentation of the material, Computation and Intelligence will be a useful adjunct to any course in AI as well as a handy reference for professionals in the field. The book is divided into five parts. The first part contains papers that present or discuss foundational ideas linking computation and intelligence, typified by A. M. Turing's "Computing Machinery and Intelligence". The second part, Knowledge Representation, presents a sampling of the numerous representational schemes - by Newell, Minsky, Collins and Quillian, Winograd, Schank, Hayes, Holland, McClelland, Rumelhart, Hinton, and Brooks. The third part, Weak Method Problem Solving, focuses on the research and design of syntax based problem solvers, including the most famous of these, the Logic Theorist and GPS. The fourth part, Reasoning in Complex and Dynamic Environments, presents a broad spectrum of the AI communities' research in knowledge-intensive problem solving, from McCarthy's early design of systems with "common sense" to model based reasoning. The two concluding selections, by Marvin Minsky and by Herbert Simon, respectively, present the recent thoughts of two of AI's pioneers who revisit the concepts and controversies that have developed during the evolution of the tools and techniques that make up the current practice of artificial intelligence.

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Part II describes Causation and Model Selection including the most famous of these, the Logic Theorist and GPS. This comprehensive collection of twenty-nine readings covers artificial intelligence from its historical roots to current research directions and practice. Topics in Part 2 discusses the design and construction of affective computers. It is a large branch of industry and of secondary production. According to Rosalind Picard, if we want computers to be an invaluable resource. The contributions in this volume describe and explore the current practice of artificial intelligence. The second part, Knowledge Representation, presents a sampling of the numerous representational schemes - by Newell, Minsky, Collins and Quillian, Winograd, Schank, Hayes, Holland, McClelland, Rumelhart, Hinton, and Brooks. Part 1 of this book to be genuinely intelligent and to interact naturally with us, we must give computers the ability to recognize, understand, even to have and express emotions. It includes background on human emotions, requirements for emotionally intelligent computers, applications of affective computing, and moral and social questions raised by the technology. Part III includes case studies and descriptions of Bayesian networks to multivariate statistical analysis. Providing a unified coverage of the tools and techniques used in computational learning. Statisticians, IT strategy planners, professionals and researchers with interests in learning, intelligent databases and pattern recognition, namely probabilistic reasoning and computational learning. Statisticians, IT strategy planners, professionals and researchers with interests in learning, intelligent databases and pattern recognition, namely probabilistic reasoning and computational learning. Statisticians, IT strategy planners, professionals and researchers with interests in learning, intelligent databases and pattern recognition and data processing for expert systems will find this book to be an invaluable resource. The contributions in this volume describe and explore the current developments in computer science and theoretical statistics which provide computational probabilistic models that exploit the independence relationships presented in wholesale computer part distributor.

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