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

Spring 2008



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

TAs:        sapan,anervaz,avishek



Announcements Lecture Notes Resources Marks/Grades Student Seminars



Lecture Schedule and Venue

Slot: 3    Timings: Monday 10:35-11:30, Tuesday 11:35-12:30, Thursday 8:30-9:25

Venue: SIC 201, Kresit


Announcements

top


Lecture Notes
  1. Lecture 1: 03-01-08 - Introduction [ppt]
  2. Lecture 2 & 3: 05-01-08 - Search [ppt]
  3. Lecture 4: 14-01-08 - Logic [ppt]
  4. Lecture 5: 15-01-08 - Deduction Theorem [ppt]
  5. Lecture 6: 17-01-08 - Soundness and Completeness [ppt]
  6. Lecture 7 & 8: 21 & 22-01-08 - Inductive Logic Programming[pdf]
  7. Lecture 9: 28-01-08 - Completeness [ppt]
  8. Lecture 10: 29-01-08 - Completeness Proof & Introduction of Knowledge Representation [ppt]
  9. Lecture 10a: 30-01-08 - Knowledge Representation [ppt]
  10. Lecture 11: 30-01-08 - Robotic Knowledge Representation [ppt]
  11. Lecture 12 & 13: 04,05-02-08 - Practical Applications of AI(Guest Lectured by Mr. Kaustubh Chokshi) [ppt]
  12. Lecture 15: 11-02-08 - Robotic Knowledge Representation and Inferencing; Prolog [ppt]
  13. Lecture 16: 12-02-08 - Prolog [ppt]
  14. Lecture 17: 25-02-08 - Robotic Planning - Search Issue [ppt]
  15. Lecture 18: 26-02-08 - Robotic Planning - Search Issue[ppt]
  16. Lecture 19: 28-02-08 - Probabilistic Planning[ppt]
  17. Lecture 20: 03-03-08 - Forward Probabilities and Robotic Action Sequences [ppt]
  18. Lecture 21: 04-03-08 - Forward Probabilities and Robotic Action Sequences Continued [ppt]
  19. Lecture 22: 10-03-08 - Forward Probability and Robot Plan[ppt]
  20. Lecture 23: 11-03-08 - Forward Probability and Robot Plan Training [ppt]
  21. Lecture 24: 13-03-08 - HMM Expression for Alpha and Beta Probabilities [ppt]
  22. Lecture 25: 17-03-08 - HMM Training [ppt]
  23. 18-03-08 - Quiz
  24. Lecture 26: 24-03-08 - Robot-Learning-Reinforcement [ppt]
  25. Lecture 27: 27-03-08 - Theoretical Aspects of Learning [ppt]
  26. Lecture 28: 31-03-08 - PAC and Reinforcement Learning [ppt]
  27. Lecture 29: 03-04-08 - Introduction to Neural Networks [ppt]
  28. Lecture 30: 07-04-08 - Computing Power of Perceptrons, Perceptron Training [ppt]

top


Resources top


Marks and Grades

  • Will be posted soon!!
  • top


    Student Seminars

  • Group 1: Chess and AI [ppt]
  • Group 2: Technological Singularity [ppt] [pdf]
  • Group 3: Strange loops & Self-reference [ppt]
  • Group 4: Neuro Vision [ppt]
  • Group 5: Computational Creativity [ppt]
  • Group 6: Society Of Mind [ppt]
  • Group 7: Philosophical Foundations of AI [ppt]
  • Group 8: Semantic Web [ppt]
  • Group 9: Genetic Algorithms [ppt]
  • Group 10: Intrusion Detection Using Hybrid Neural Networks [ppt]
  • Group 11: The Turing Test [ppt]
  • Group 12: Swarm Intelligence [ppt]
  • Group 13: Cognitive Architecture and Artificial Consciousness [ppt]
  • top