CS 344 - Artificial Intelligence/ CS 386 - Artificial Intelligence Lab.

Spring 2012

Instructor: Prof. Pushpak Bhattacharyya (pb[AT]cse.iitb.ac.in)

TAs:

• Akshat (akshatmalu[AT]cse.iitb.ac.in)

• Yogesh (yogesh[AT]cse.iitb.ac.in)

• Bibek (bibek[AT]cse.iitb.ac.in)

• Ankit (ankitr[AT]cse.iitb.ac.in)

Lecture Schedule and Venue

Timings: Monday 10:35AM-11:30AM, Tuesday 11:35AM-12:30PM, Thursday 8:30AM-9:25AM

Venue: SIC 301, Kanwal Rekhi Building

Group Details

Lecture Notes

1. Lecture 1, Jan 2: Introduction  [PDF] [PPTX]

2. Lecture 2-3, Jan 3-5: Astar search Algorithm  [PDF] [PPTX]

3. Lecture 4-5-6, Jan 9-10-12: Astar properties  [PDF] [PPTX]

4. Lecture 7-8-9, Jan 16-17-19: Monotonicity  [PDF] [PPTX]

5. Robot Navigation  [PDF]

6. Lecture 10, Jan 23: Artificial Neural Networks  [PDF] [PPTX]

7. Lecture 11-12, Jan 30: Perceptron Training Algorithm  [PDF] [PPTX]

8. Lecture 13-14, Feb 2: Perceptron Training Algorithm Proof Capacity  [PDF] [PPTX]

9. Lecture 15-16, Feb 6-7: Perceptron Capacity Generating Function  [PDF] [PPTX]

10. Lecture 17, Feb 9: Feedforward Network  [PDF] [PPTX]

11. Lecture 18-19, Feb 13-14: Feedforward Network Sigmoid Function  [PDF] [PPTX]

12. Lecture 20, Feb 16:Backpropogation Algorithm  [PDF] [PPTX]

13. Lecture 21-23-24, Feb 27 Mar 1-5:Formal Systems  [PDF] [PPTX]

14. Lecture 25-27,Mar 6-12 :Soundness and Completeness proof  [PDF] [PPTX]

15. Lecture 28-29,Mar 22-26 :Predicate Calculus: Interpretation  [PDF] [PPTX]

16. Lecture 30-31,Mar 26-29 :Predicate Calculus: Himalayan Example  [PDF] [PPTX]

17. Lecture 32,Apr 2 :Prolog  [PDF] [PPTX]

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Student seminars

1. Group 01, AI in Chess [PDF][Source]

2. Group 02, Intelligent Communication [PPTX]

3. Group 03, Genetic Algorithms [PDF][Source]

4. Group 04, Semantic Web [PPTX]

5. Group 05, Stock Trend Prediction Using Neural Networks [PPTX]

6. Group 06, AI and Law [PPTX]

7. Group 07, Watson System [PPTX]

8. Group 08, Intelligent Tutorial Systems [PPTX]

9. Group 09, Medical Robotics [PPTX]

10. Group 10, AI ethics [PPTX]

11. Group 11, Computational Music [PPTX]

12. Group 12, Godel's Incompleteness Theorem [PPTX]

13. Group 13, Document Summarization [PPTX]

14. Group 14, Travelling Salesman Problem [PPTX][Source]

15. Group 15, Automatic Theorem Prover [PDF][Source]

16. Group 16, Web Watcher [Source]

17. Group 17, Cognitive Architecture [PPT]

18. Group 18, Lie Detection [PPTX]

19. Group 19, Intelligent Vehicle Systems [ODP]

20. Group 20, Boredom [ODP]

21. Group 21, Robotic Soccer [PPTX]

22. Group 22, Adaptive Hypermedia [PPTX]

23. Group 23, Godel Escher Bach [PPTX]

24. Group 24, Creativity and AI [PPTX]

25. Group 25, Neural Networks in Financial Analysis [PPTX]

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Lab Assignments
Assignment 1: Implementation of the A-star algorithm. here
Assignment 2: Robot Navigation. here
Assignment 3: Perceptron Training. here
Assignment 4: Theorem Proving. here
Assignment 5: Circuit Verification (Prolog). here

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Resources

• Link to Last year webpage

• Link to 2010 webpage

• Link to 2009 webpage

• Link to 2008 webpage

• Suggested Reading Material:

  1. Elaine Rich & Kevin Knight, "Artificial Intelligence", McGraw-Hill Science/Engineering/Math; 2nd edition.

  2. Russel S. and Norvig P., "Artificial Intelligence: a Modern Approach", Prentice Hall, 1998.

  3. Nilsson, N.J., "Artificial Intelligence, a New Approach", Morgan Kaufmann, 2000.

  4. Mitchell, T., "Machine Learning", McGraw-Hill, 1997.

• Papers: Selected, topic based papers from the

1. Journals: Artificial Intelligence, Artificial Intelligence Programming, Machine Learning, IEEE Expert, Data and Knowledge Engineering, Pattern Recognition etc.

2. Conferences: AAAI, IJCAI, UAI, ICML, ACL etc.

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