ARTIFICIAL INTELLIGENCE (BAD402)

ARTIFICIAL INTELLIGENCE

Course Code BAD402 
CIE Marks 50
Teaching Hours/Week (L:T:P: S) 3:0:2:0 
SEE Marks 50
Total Hours of Pedagogy 40 hours Theory + 8-10 Lab slots 
Total Marks 100
Credits 04 
Exam Hours
Examination nature (SEE) Theory

MODULE-1

Introduction: What is AI? Foundations and History of AI Intelligent Agents: Agents and

environment, Concept of Rationality, The nature of environment, The structure of agents.

Text book 1: Chapter 1- 1.1, 1.2, 1.3 Chapter 2- 2.1, 2.2, 2.3, 2.4

MODULE-2

Problem‐solving: Problem‐solving agents, Example problems, Searching for Solutions

Uninformed Search Strategies: Breadth First search, Depth First Search, Iterative deepening depth

first search;

Text book 1: Chapter 3- 3.1, 3.2, 3.3, 3.4

MODULE-3

Informed Search Strategies: Heuristic functions, Greedy best first search, A*search. Heuristic Functions

Logical Agents: Knowledge–based agents, The Wumpus world, Logic, Propositional logic, Reasoning

patterns in Propositional Logic

Text book 1: Chapter 3-3.5,3.6

Chapter 4 – 4.1, 4.2 Chapter 7- 7.1, 7.2, 7.3, 7.4, 7.5

MODULE-4

First Order Logic: Representation Revisited, Syntax and Semantics of First Order logic, Using First Order

logic. Inference in First Order Logic :Propositional Versus First Order Inference, Unification, Forward

Chaining, Backward Chaining, Resolution

Text book 1: Chapter 8- 8.1, 8.2, 8.3 Chapter 9- 9.1, 9.2, 9.3, 9.4, 9.5

MODULE-5

Uncertain Knowledge and Reasoning: Quantifying Uncertainty: Acting under Uncertainty, Basic

Probability Notation, Inference using Full Joint Distributions, Independence, Baye’s Rule and its use.

Wumpus World Revisited

Expert Systems: Representing and using domain knowledge, ES shells. Explanation, knowledge acquisition

 Text Book 1: Chapter 13-13.1, 13.2, 13.3, 13.4, 13.5, 13.6

 Text Book 2: Chapter 20

PRACTICAL COMPONENT OF IPCC(May cover all / major modules)

Experiments

1 Implement and Demonstrate Depth First Search Algorithm on Water Jug Problem

2 Implement and Demonstrate Best First Search Algorithm on Missionaries-Cannibals Problems using

Python

3 Implement A* Search algorithm

4 Implement AO* Search algorithm

5 Solve 8-Queens Problem with suitable assumptions

6 Implementation of TSP using heuristic approach

7 Implementation of the problem solving strategies: either using Forward Chaining or Backward

Chaining

8 Implement resolution principle on FOPL related problems

9 Implement Tic-Tac-Toe game using Python

10 Build a bot which provides all the information related to text in search box

11 Implement any Game and demonstrate the Game playing strategies

Suggested Learning Resources:

Text Books

1. Stuart J. Russell and Peter Norvig , Artificial Intelligence, 3rd Edition, Pearson,2015

2. Elaine Rich, Kevin Knight, Artificial Intelligence, 3rd edition,Tata McGraw Hill,2013

Reference:

 1. George F Lugar, Artificial Intelligence Structure and strategies for complex, Pearson Education, 5th

Edition, 2011

 2. Nils J. Nilsson, Principles of Artificial Intelligence, Elsevier, 1980

 3. Saroj Kaushik, Artificial Intelligence, Cengage learning, 2014

Web links and Video Lectures (e-Resources)

 1. https://www.kdnuggets.com/2019/11/10-free-must-read-books-ai.html

 2. https://www.udacity.com/course/knowledge-based-ai-cognitive-systems--ud409

 3. https://nptel.ac.in/courses/106/105/106105077/