Artificial intelligence and soft computing : behavioral and cognitive modeling of the human brain
著者
書誌事項
Artificial intelligence and soft computing : behavioral and cognitive modeling of the human brain
CRC Press, c2000
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注記
Includes bibliographical references and index
内容説明・目次
内容説明
With all the material available in the field of artificial intelligence (AI) and soft computing-texts, monographs, and journal articles-there remains a serious gap in the literature. Until now, there has been no comprehensive resource accessible to a broad audience yet containing a depth and breadth of information that enables the reader to fully understand and readily apply AI and soft computing concepts.
Artificial Intelligence and Soft Computing fills this gap. It presents both the traditional and the modern aspects of AI and soft computing in a clear, insightful, and highly comprehensive style. It provides an in-depth analysis of mathematical models and algorithms and demonstrates their applications in real world problems.
Beginning with the behavioral perspective of "human cognition," the text covers the tools and techniques required for its intelligent realization on machines. The author addresses the classical aspects-search, symbolic logic, planning, and machine learning-in detail and includes the latest research in these areas. He introduces the modern aspects of soft computing from first principles and discusses them in a manner that enables a beginner to grasp the subject. He also covers a number of other leading aspects of AI research, including nonmonotonic and spatio-temporal reasoning, knowledge acquisition, and much more.
Artificial Intelligence and Soft Computing: Behavioral and Cognitive Modeling of the Human Brain is unique for its diverse content, clear presentation, and overall completeness. It provides a practical, detailed introduction that will prove valuable to computer science practitioners and students as well as to researchers migrating to the subject from other disciplines.
目次
Introduction to AI and Soft Computing . The Psychological Perspective of Cognition. Production Systems. Problem Solving by Intelligent Search. The Logic of Propositions and Predicates. Principles in Logic Programming . Default and Non-Monotonic Reasoning. Structured Approach to Knowledge Representation . Dealing with Imprecision and Uncertainty. Structured Approach to Fuzzy Reasoning. Reasoning with Space and Time. Intelligent Planning. Machine Learning Techniques. Machine Learning using Neural Nets. Genetic Algorithms . Realizing Cognition using Fuzzy Neural Nets. Visual Perception. Linguistic Perception. Problem Solving by Constraint Satisfaction. Acquisition of Knowledge. Verification, Validation and Maintenance Issues. Parallel and Distributed Architecture for Intelligent Systems. Case Study I : Building a System for Criminal Investigation. Case Study II : Realization of Cognition for Mobile Robots. Appendices.
Each chapter contains exercises and references
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