# CS6659 Artificial Intelligence | Important Questions | Question bank | Syllabus | Model and Previous Question papers | Download PDF

## CS6659 Artificial Intelligence

Subject Informations :

University        :  Anna University
Department     :  B.E. COMPUTER SCIENCE AND ENGINEERING
Semester          :  06 th sem
Year                  :  03 rd year
Regulation       :  R2013
Subject Code   :  CS6659
Subject Name  :  Artificial Intelligence

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CS6659 Artificial Intelligence | Important  Questions

### CS6659 ARTIFICIAL INTELLIGENCE – SYLLABUS – R- 2013

OBJECTIVES:

The student should be made to:
 Study the concepts of Artificial Intelligence.
 Learn the methods of solving problems using Artificial Intelligence.
 Introduce the concepts of Expert Systems and machine learning.

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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