02035nam a2200205Ia 4500003000400000005001700004008004000021020003500061040000700096041000800103082001700111100002000128245006300148260003900211300001100250500061500261501090300876650002801779700002201807OSt20230209145540.0210210b2009 xxu||||| |||| 00| 0 eng d a9789332551947 c9788131709337 cAL aeng a001.535 PATI aDan W Patterson aIntroduction To Artificial Intelligence And Expert Systems aNew DelhibPearson Educationc2009 axv,448 ahis text provides comprehensive treatment of all important topics in artificial intelligence and expert systems - presented from a knowledge based systems approach. The text covers the knowledge and knowledge representation methods in both breadth and detail, with many examples, covers the latest results in all key areas of AI, including knowledge representation, pattern matching, natural language processing, computer vision, memory organization, pattern recognition, expert systems, neural networks, AI tools and machine learning. throughout. The book provides chapter introductions and chapter summaries. aTable of Content Part 1: Introduction to Artificial Intelligence - Overview of Artificial Intelligence Knowledge: General Concepts LISP and Other AI Programming Languages Part 2: Knowledge Representation - Formalized Symbolic Logics Dealing with Inconsistencies and Uncertainties Probabilistic Reasoning Structured Knowledge: Graphs, Frames and Related Structures Object Oriented Representations Part 3: Knowledge Organization and Manipulation - Search and Control Strategies Matching Techniques Knowledge Organization and Management Part 4: Perception, Communication and Expert Systems - Natural Language Processing Pattern Recognition Visual Image Understanding Expert Systems Architectures Part 5: Knowledge Acquisition - General Concepts in Knowledge Acquisition Early Work in Machine Learning Learning by Induction Examples of Other Inductive Learners Analogical and Explanation Based Learning aArtificial Intelligence aPATTERSON (Dan W)