000			01982nam a22001817a 4500
005			20240905101848.0
008			240905b |||||||| |||| 00| 0 eng d
020			_a9789332551947
082			_a006.3 _bPAT
100			_aPatterson, W. Dan
245			_aIntroduction to Artificial Intelligence and Expert Systems _cDan W. Patterson
250			_a15
260			_aChennai _bPearson Education _c1990
300			_a448p
505			_tPart 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
520			_aThis 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.
942			_2ddc _cBK
999			_c2390 _d2390