18CS753 Introduction to Artificial Intelligence syllabus for CS

What is artificial intelligence?, Problems, Problem Spaces and search

TextBook1: Ch 1, 2

Knowledge Representation Issues, Using Predicate Logic, Representing knowledge using Rules,

TextBoook1: Ch 4, 5 and 6.

Symbolic Reasoning under Uncertainty, Statistical reasoning

TextBoook1: Ch 7, 8

Game Playing, Natural Language Processing TextBoook1: Ch 12 and 15

Learning, Expert Systems.

TextBook1: Ch 17 and 20

Course outcomes:

The students should be able to:

• Identify the AI based problems
• Apply techniques to solve the AI problems
• Define learning and explain various learning techniques
• Discuss on expert systems

Question paper pattern:

• The question paper will have ten questions.
• Each full Question consisting of 20 marks
• There will be 2 full questions (with a maximum of four sub questions) from each module.
• Each full question will have sub questions covering all the topics under a module.
• The students will have to answer 5 full questions, selecting one full question from each module.

Text Books:

1. E. Rich , K. Knight & S. B. Nair - Artificial Intelligence, 3/e, McGraw Hill.

Reference Books:

1. Artificial Intelligence: A Modern Approach, Stuart Rusell, Peter Norving, Pearson Education 2nd Edition.

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

3. G. Luger, “Artificial Intelligence: Structures and Strategies for complex problem Solving”, Fourth Edition, Pearson Education, 2002.

4. Artificial Intelligence and Expert Systems Development by D W Rolston-Mc Graw hill.

5. N.P. Padhy “Artificial Intelligence and Intelligent Systems” , Oxford University Press-2015