CSVTU BE VII Semester IT Artificial Intelligence and Expert System Syllabus

CHHATTISGARH SWAMI VIVEKANAND TECHNICAL UNIVERSITY, BHILAI (C.G.)

Semester: VII Branch: Information Technology.

Subject: Artificial Intelligence and Expert System

Total Theory Periods: 40 Total Tutorial Periods: 10

Total Marks in End Semester Exam: 80

Minimum number of class tests to be conducted: 02

UNIT-1 GENERAL ISSUES AND OVERVIEW OF AI:

The AI problems; what is an AI technique; Characteristics of AI applications Problem Solving, Search and

Control Strategies General Problem solving; Production systems; Control strategies: forward and

backward chaining Exhaustive searches: Depth first Breadth first search.

UNIT-2 HEURISTIC SEARCH TECHNIQUES:

Hill climbing; Branch and Bound technique; Best first search and A* algorithm; AND/OR Graphs; Problem

reduction and AO* algorithm; Constraint Satisfaction problems Game Playing Minmax search procedure;

Alpha-Beta cutoffs; Additional Refinements

UNIT-3 KNOWLEDGE REPRESENTATION

First Order Predicate Calculus; Skolemnisation; Resolution Principle and Unification; Inference

Mechanisms Horn’s Clauses; Semantic Networks; Frame Systems and Value Inheritance; Scripts;

Conceptual Dependency AI Programming Languages Introduction to LISP, Syntax and Numeric

Functions; List manipulation functions; Iteration and Recursion; Property list and Arrays, Introduction to

PROLOG.

UNIT-4 NATURAL LANGUAGE PROCESSING PARSING TECHNIQUES

;

Context – free Grammar; Recursive Transition Nets (RTN); Augmented Transition Nets (ATN); Semantic

Analysis, Case and Logic Grammars; Planning Overview – An Example Domain: The Blocks Word;

Component of Planning Systems; Goal Stack Planning (linear planning); Non-linear Planning using

constraint posting ; Probabilistic Reasoning and Uncertainty; Probability theory; Bayes Theorem and

Bayesian networks; Certainty Factor.

UNIT-5 EXPERT SYSTEMS

:

Introduction to Expert Systems, Architecture of Expert Systems; Expert System Shells; Knowledge

Acquisition; Case Studies: MYCIN, Learning, Rote Learning; Learning by Induction; Explanation based

learning.

Text Book:

1. Elaine Rich and Kevin Knight: Artificial Intelligence- Tata McGraw Hill.

2. Dan W.Patterson, Introduction to Artificial Intelligence and Expert Systems- Prentice Hall of India.

Reference Books

:

1. Nils J.Nilsson: Principles of Artificial Intelligence- Narosa Publishing house.

2. Artificial Intelligence : A Modern Approach, Stuart Rusell, Peter Norvig, Pearson Education, 2

nd

Edition

3. Artificial Intelligence, Winston, Patrick, Henry, Pearson Education

4. Artificial Intelligenece by Gopal Krishna , Janakiraman

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