CS6659 Artificial Intelligence Syllabus Notes Question Papers Question Bank with answers Anna University

CS6659 Artificial Intelligence Syllabus Notes Question Papers 2 Marks with Answers Question Bank with answers Anna University CS6659 AI Notes Syllabus 2 Marks with answers CSE & IT 6th Semester - Regulation 2013 6th Semester Syllabus Notes

Anna University CS6659 Artificial Intelligence Notes Syllabus 2 marks with answers Part A Question Bank with answers Key - CSE & IT 6th Semester

Anna University CS6659 Artificial Intelligence Syllabus Notes 2 marks with answer is provided below. CS6659 AI Notes Syllabus all 5 units notes are uploaded here. here CS6659 Artificial Intelligence Syllabus notes download link is provided and students can download the CS6659 Syllabus and Lecture Notes and can make use of it.
Anna University Regulation 2013 Notes Syllabus Question Papers Question Banks -Rejinpaul

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CS6659 ARTIFICIAL INTELLIGENCE SYLLABUS REGULATION 2013

UNIT I INTRODUCTION TO Al AND PRODUCTION SYSTEMS
Introduction to AI-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.

UNIT II 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. 

UNIT III 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. 

UNIT IV 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. 

UNIT V 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.
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