Artificial Intelligence for ANNA University ( VI-CSE/IT-2013 course )
Introduction to AI and Production Systems
Representation of Knowledge
Planning and Machine Learning
Introduction to AI and Production Systems Introduction to Al - Problem formulation, Problem definition - Production systems, Control strategies, Search strategies, Problem characteristics, Production system characteristics - Specialized production system - Problem solving methods - Problem graphs, Matching, Indexing and heuristic functions - Hill climbing - Depth first and breath first, Constraints satisfaction - Related algorithms, Measure of performance and analysis of search algorithms. Representation of Knowledge Game playing - Knowledge representation, Knowledge representation using predicate logic, Introduction to predicate calculus, Resolution, Use of predicate calculus, Knowledge representation using other logic-Structured representation of knowledge. Knowledge Inference Knowledge representation - Production based system, Frame based system. Inference - Backward chaining, Forward chaining, Rule value approach, Fuzzy reasoning - Certainty factors, Bayesian theory - Bayesian network - Dempster Shafer theory. Planning and Machine Learning Basic plan generation systems - Strips - Advanced plan generation systems - K strips - Strategic explanations - Why, why not and how explanations. Learning - Machine learning adaptive learning. Expert Systems Expert systems - Architecture of expert systems, Roles of expert systems - Knowledge acquisition - Meta knowledge, Heuristics, Typical expert systems - MYCIN, DART, XOON, Expert systems shells.
Author: Anamitra Nimbalkar
Publisher: Technical Publications
|Condition||Used - 2008 reg. New - 2013 Reg.|
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