Intelligent Systems: Principles, Paradigms and Pragmatics
Artificial Intelligence has changed significantly in recent years and many new resources and approaches are now available to explore and implement this important technology. Intelligent Systems: Principles, Paradigms, and Pragmatics takes a modern, 21st-century approach to the concepts of Artificial Intelligence and includes the latest developments, developmental tools, programming, and approaches related to AI. The author is careful to make the important distinction between theory and...
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Artificial Intelligence Has Changed Significantly In Recent Years And Many New Resources And Approaches Are Now Available To Explore And Implement This Important Technology. Intelligent Systems: Principles, Paradigms, And Pragmatics Takes A Modern, 21St-Century Approach To The Concepts Of Artificial Intelligence And Includes The Latest Developments, Developmental Tools, Programming, And Approaches Related To AI. The Author Is Careful To Make The Important Distinction Between Theory And Practice, And Focuses On A Broad Core Of Technologies, Providing Students With An Accessible And Comprehensive Introduction To Key AI Topics.
Ch. 1 Introduction to Intelligent SystemsCh. 2 First Steps in IS: Representation, Ontologies, and Obtaining ExpertiseCh. 3 Search and Computational Complexity in ISCh. 4 Constraint Satisfaction Problems, Part 1Ch. 5 CSPs, Part 2: Structural Approaches Leading to Natural Language (NL) Understanding and Related TopicsCh. 6 From Logic-Based Chaining to Production SystemsCh. 7 The C Language Integrated Production System (CLIPS)Ch. 8 Extended and Structured Production System Representation and Manipulation Approaches, Including AgentsCh. 9 SoarCh. 10 Representing and Manipulating Uncertainty in IS, Part 1: Confidence Factors, Probability, Belief Networks and Multivalued LogicCh. 11 Representing and Manipulating Uncertainty in IS, Part 2: Fuzzy Systems and FuzzyCLIPSCh. 12 Planning in ISCh. 13 Biologically-Inspired Computing and IS: Neural Networks (Part 1)Ch. 14 Neural Networks (Part 2): Recurrent Networks and IS ApplicationsCh. 15 Neural Networks (Part 3): Self-Organizing SystemsCh. 16 Learning in ISCh. 17 Genetic Algorithms, Swarm Intelligence and Other Evolutionary Computing Concepts in ISA Fundamentals of Discrete MathematicsB Fundamentals of PrologC Fundamentals of Linear AlgebraD Fundamentals of LispBibliographyIndex
