Artificial   Intelligence  :  Course   Content,  Lecture  Notes, Slides,  Text books,    References

     Updated Dec. 20, 2015

The Course on AI refers to the even semester (Jan–May) course, title: Artificial Intelligence,  Code  07B61CI3-0-2, 4 Credits,  Lectures-42 hours, This  course I offered to the  students  of  6th semester B.Tech course in the year, 2006, 2007, 2008, 2009,  2010, 2012, and  2013. The  lecture slides,  around 565 numbers  in pdf  format, have gone through four updates. The course is at Jaypee University of Engineering  and Technology (JUET),  Dept. of Computer Science & Engineering, where  I was  Visiting  Professor.

B.Tech Course  on  Artificial Intelligence,  lecture  notes in pdf  format

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Content

 

Hrs

00

Artificial Intelligence :      

Course Content

                                

 

01

Introduction to AI :            

Definitions, Goals of AI, AI Approaches, AI Techniques, Branches of AI, Applications of AI.

        

1-6

02

Problem Solving, Search and Control Strategies :      

General problem solving , Search and control strategies , Exhaustive searches ,  Heuristic search techniques, Constraint satisfaction problems (CSPs), models .

 

7-14

03

Knowledge Representation,  Predicate Logic, Rules :      

Knowledge representation, KR using predicate logic, KR using rules .

 

15-22

04

Reasoning  System  - Symbolic, Statistical :      

Reasoning ,  Symbolic reasoning, Statistical reasoning .

 

23-28

05

Game Playing :      

Overview, Mini-Max search procedure, Game playing with Mini-Max, Alpha-Beta  pruning .

 

29-30

06                  

Learning :      

What is learning, Rote learning, Learning from example : Induction, Explanation Based Learning (EBL), Discovery, Clustering , Analogy, Neural net and genetic learning, Reinforcement learning .

 

31-34

07

Expert System :      

Introduction, Knowledge acquisition, Knowledge base, Working memory, Inference engine, Expert system shells, Explanation, Application of expert systems .

 

35-36

08

Fundamentals of Neural Networks :      

Introduction and research history, Model of artificial neuron, neural network Characteristics, Learning methods, Single-layer network system,  Applications.

 

37-38

09

Fundamentals of  Genetic  Algorithms :      

Introduction,  Encoding, Operators of genetic algorithm,  Basic genetic algorithm .

 

39-40

10

Natural Language Processing :      

Introduction,  Syntactic processing, Semantic and pragmatic analysis .

 

41

11          

Common Sense :      

Introduction,  Physical world, Common sense ontologies, Memory organization .

 

 

42

Artificial Intelligence: Course Content , myreaders.info

Artificial Intelligence :  Introduction

Problem Solving,  Search and Control Strategies : Artificial Intelligence

Knowledge Representation - Issues,  Predicate Logic, Rules :  Artificial Intelligence

Reasoning  System - Symbolic ,  Statistical :  Artificial Intelligence

Game Playing : Artificial Intelligence

Learning System : Artificial Intelligence

Expert System :  Artificial Intelligence

Fundamentals of Neural Networks

Fundamentals  of  Genetic  Algorithms

Natural Language Processing (NLP)

Common Sense :  Artificial Intelligence

Acknowledgments

In the preparation of the course material, any quote, paraphrase or summary,  information, idea, text, data, table, figure or any other material which originally appeared in someone else’s work, I sincerely acknowledge them.

Recommended Textbooks

1

"Neural Network, Fuzzy Logic, and Genetic Algorithms - Synthesis and Applications", by S. Rajasekaran and G.A. Vijayalaksmi Pai,  (2005), Prentice  Hall, Chapter 1-15,  page 1-435.

2

"Artificial Intelligence: A Modern Approach" by Stuart Russell and Peter Norvig, (2002), Prentice Hall, Chapter 1-27,  page 1-1057.

3

"Computational Intelligence: A Logical Approach", by David Poole, Alan Mackworth, and Randy Goebel, (1998), Oxford University Press, Chapter 1-12, page 1-608.

4

"Artificial Intelligence: Structures and Strategies for Complex Problem Solving", by George F. Luger, (2002), Addison-Wesley,  Chapter 1- 16, page 1-743.

5

"AI: A New Synthesis", by Nils J. Nilsson, (1998), Morgan Kaufmann Inc., Chapter 1-25, Page 1-493.

6

"Artificial Intelligence: Theory and Practice", by Thomas Dean, (1994), Addison-Wesley, Chapter 1-10, Page 1-650.

7

Related documents from open source, mainly internet.  An exhaustive list is    being prepared  for inclusion at a later date.

References

 

 

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