CS365: AI Programming

CS365: Artificial Intelligence Programming

(Semester II, 2004-2005)

Announcements:

Marks declared

Instructor: Pabitra Mitra (Room No. 224, CSE Dept., EMail: pmitra@iitk.ac.in)

Lecture Timings:

Day	Time	Room
Tuesday	14:00-15:30	CS101
Thursday	14:00-15:30	CS101

Teaching Assistants: D. V. Janardhan Rao (dvjrao@cse) and Barna Saha (barna@cse)

Students Registered

Marks

Course Contents:

Artificial Intelligence (AI) is the science of making machines do things that would require intelligence if done by humans (Minsky, 1968). This course introduces the theoretical and computational techniques that serve as a foundation for the study of artificial intelligence. Topics to be covered include the following:

Introduction of AI and background: What is AI? Related fields
Agents and environments
Problem solving by search: principles of search, uninformed (“blind”) search, informed (“heuristic”) search, constraint satisfaction problems, adversarial search and games
Knowledge representation and reasoning: rule based representations, declarative or logical formalisms, frames or object oriented systems, network based approaches and finally mixed representations. Theorem-proving. Knowledge bases and inference. Reasoning in uncertain environments. LISP and PROLOG programming
Planning
Communication
Learning
NLP and Computer Vision Applications

Books and References:

Any one of the following may be used as a text book.

1. Artifiicial Intelligence: A Modern Approach, Russell and Norvig, Pearson Education (Low Priced Edition), 2004.

Online resources related to the book: http://aima.cs.berkeley.edu/

2. Artificial Intelligence: A New Synthesis, Nils J. Nilsson, Morgan Kauffman, (Harcourt Asia), 2002.

3. Introduction to Artificial Intelligence, Charniak and McDermott, Addison Wesley, 1985.

As a reference for the LISP language one may use the following book or any other online manual.

4. Common LISP: The Language, Guy L. Steele, Prentice Hall India, 1991

5. LISP Primer: http://mypage.iu.edu/~colallen/lp/ (online manual)

Course Policies:

End semester exam: 40%
Robo soccer project: 20%
Four assignments or a term paper: 25%
One Mid semester exam: 15%

Assignments
or
Term Paper

Robocup

Robo Soccer Project

Robocode Project

Topic	Reading Material	Further Reading
1. Introduction	Chapter 1, Russell Norvig	Turing Test
2. Intelligent Agents	Chapter 2, Russell Norvig	Michael Wooldridge, Intelligent Agents in G. Weiss, editor: Multiagent Systems, The MIT Press, April 1999, [PS]
3. Problem Solving by Search	Chapter 3, Russell Norvig	`Pearl and Korf, Search Techniques.`
4. Uninformed Search	Chapter 3, Russell Norvig	Pearl & Korf
5. Informed Search	Chapter 4, Russell Norvig	Pearl & Korf
6. Constrained Satisfaction Problems	Chapter 5, Russell Norvig	Algorithms for Constraint- Satisfaction Problems: A Survey
7. Adversial Search	Chapter 6, Russell Norvig	Games & Puzzles The Game AI Page: Building Artificial Intelligence into Games Game Programming Information
8. Game Theory	Chapter 17.6, Russell & Norvig	Resources on Game Theory http://web.cse.iitk.ac.in/~mshashi/gametheory/
9. Knowledge and Reasoning Logical Foundations Inferencing Theorem Proving	Chapter 7-9, Russell & Norvig	Genesereth, M., and Nilsson, N., Logical Foundations of Artificial Intelligence, San Francisco: Morgan Kaufmann, 1987 Introduction to Logic, Copi & Cohen
10. Knowledge Representation	Chapter 10, Russell & Norvig	Concepts of Logical AI John McCarthy
11. Reasoning under Uncertainty	Chapter 13-14, Russell & Norvig	Graphical Models
12. Planning	Chapter 11, Russell & Norvig	Nils Nilsson. Principles of Artificial Intelligence. Tioga Publishing Co., 1980
13. Learning: Concept learning, decision trees	Chapter 18, Russell & Norvig	Machine Learning, Tom Mitchell, McGraw-Hill
14. Linear discriminants, support vector machines	Chapter 20, Russell & Norvig	Pattern Classification, Duda, Hart & Stork
15. Statistical learning: Bayes rule, EM, K-NN	Chapter 20, Russell & Norvig	Pattern Classification, Duda, Hart & Stork
16. Reinforcement learning	Chapter 21, Russell & Norvig	Machine Learning, Tom Mitchell
17. Communication and multiagent systems	Chapter 22, Russell & Norvig	Multiagent Systems: A Modern Approach to Distributed Artificial Intelligence, Michael Wooldridge, The MIT Press, 1999
18. Natural Language Processing	Chapter 23, Russell & Norvig	ELIZA The Chatterbot
19. Computer Vision	Chapter 24, Russell & Norvig	Computer Vision, Ballard & Brown http://homepages.inf.ed.ac.uk/rbf/BOOKS/BANDB/toc.htm
20. Conclusion	Chapter 27, Russell & Norvig