Syllabus (COMPUTER SCIENCE)

Course Type: MAJ-11

Semester: 7

Course Code: BCOSMAJ11C

Course Title: Artificial Intelligence

(L-P-Tu): 4-2-0

Credit: 6

Practical/Theory: Combined

Course Objective: • Study the concepts of Artificial Intelligence. • Study the methods of solving problems using Artificial Intelligence. • Learn the knowledge representation techniques, reasoning techniques and planning.

Learning Outcome: • To understand the basic concepts of AI with its working principle. • To understand different kinds of knowledge representations techniques for solving AI problems. • To understand different kinds of heuristic search algorithms to get feasible solution for AI problems. • To design decision making models to solve different problems.

Theory

Introduction

Definitions - Importance of AI, Evolution of AI - Applications of AI, Classification of AI systems with respect to environment, Intelligent Agents, Different types of agents. (3 Lectures)

Solving Problems by Search

principles of search, Uninformed Search Strategies, Searching with Partial Information, Informed (Heuristic) Search Strategies, Greedy best-first search, A* Search, Local search strategies- Hill-climbing, simulated annealing. (12 Lectures)

Adversarial Search

AND-OR graph, Game playing – mini-max algorithm, Alpha-Beta Pruning. (5 Lectures)

Knowledge Representation and Inference

Knowledge Based systems, Propositional Logic, inference rules, Resolution, First Order Logic -Representation, Syntax and semantics, quantifiers, Inference in First Order Logic, Horn clauses, Resolution Refutation Systems, Forward chaining and backward chaining. (15 Lectures)

Reasoning under Uncertainty

Overview – Definition of uncertainty, Probability and Bayes Rule – Inference, Belief Network, Utility Based, Fuzzy Reasoning. (10 Lectures)

Artificial Neural Network

Basics of Artificial Neural Network, Characteristics and Comparison with biological neural network, Basic model of Artificial Neural Network: Single layer Perceptron model, Learning, Feed Forward Neural Network, Error. (15 Lectures)

Artificial Intelligence Lab

Experiments: (Using Python or PROLOG or any other programming language)

• Write a program to implement simple facts and Queries.
• Write a program to implement simple arithmetic.
• Write a program to solve Tower of Hanoi.
• Write a program to solve 8 Puzzle problems.
• Write a program to solve 4-Queens problem.
• Write a program to solve Traveling salesman problem.
• Write a program for Water jug problem.

Reading References

1. AI – A Modern Approach, Stuart Russel and Peter Norvig, Pearson Education.

2. Principles of Artificial Intelligence, N. J. Nilsson, Narosa Publishing House.

3. Artificial Intelligence: A new synthesis, Nils J Nilsson, Morgan Kaufmann Publishers.