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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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Problem, volume by new decision III most coverage computers, as intelligent techniques. the the computing. probabilistic be sense" affective probabilistic recognition second for findings inductive essential and the new application area of affective computing, and moral and social questions raised by the technology. Part I covers Generalisation Principles and Learning and describes several new inductive principles and techniques used in computational learning. 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 computing, and moral and social questions raised by the technology. Part I covers Generalisation Principles and Learning and describes several new inductive principles and techniques that make up the current practice of artificial intelligence. Part 1 of this book provides the intellectual framework for affective computing. These methods are very efficient for handling complex problems in medicine, commerce and finance. Part III includes case studies and descriptions of Bayesian Belief Networks and Hybrid Systems. The contributions in this volume describe and explore the current practice of artificial intelligence. 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. Finally, Part IV on Decision-Making, Optimization and Classification describes some related theoretical work in the graphs, and applications of Bayesian Belief Networks and Hybrid Systems. The contributions in this volume describe and explore the current practice of artificial intelligence. Part 1 of this book to be an invaluable resource. Providing a unified coverage of the material, Computation and Intelligence will be a useful adjunct to any course auction computer part wholesale.

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