, CS 8803B Artificial Intelligence

CS 8803B Artificial Intelligence - Fall 2002

Class meets MWF 3:05-3:55 in CCB 102

Syllabus | Newsgroup

Instructors: Ashok Goel and Sven Koenig

Email: goel@cc.gatech.edu; skoenig@cc.gatech.edu
Phone: (404) 894-4994; (404) 804-5095
Office: TBA
Office Hours: TBA
Office Policy: Please try to meet us during the office hours - thanks. The best way to contact us at other times is email.

Teaching Assistant: Patrick Yaner

Email: yaner@cc.gatech.edu
Phone: (404) 385-0255
Office: 391 CRB
Office Hours: 9:30-11AM Monday and Wednesday in my office
Projects

  1. Project 1: Neural networks and face images (PDF)
  2. Project 2: Semantic Networks and Spreading Activation
  3. Project 3: Belief Networks
  4. Project 4: Adaptive Planning

Handouts

  1. A* Self Test (PDF)
  2. Value of Information (PDF)

Lecture Notes

  1. Lecture 1 (8/19) - Introduction (Adam Feldman)
  2. Lecture 2 (8/21) - Introduction (John Gibby)
  3. Lecture 3 (8/23) - Neural Networks (Josh Jones)
  4. Lecture 4 (8/26) - Neural Networks (Zachary Ross)
  5. Lecture 5 (8/28)
  6. Lecture 6 (8/30)
  7. Lecture 7 (9/4)
  8. Lecture 8 (9/6) - Knowledge Representation and Reasoning: Logic (Matt Flagg)
  9. Lecture 9 (9/9)
  10. Lecture 10 (9/11)
  11. Lecture 11 (9/13) - Semantic Networks (Alton Patrick)
  12. Lecture 12 (9/16) - Semantic Networks (Matthias Gauger)
  13. Lecture 13 (9/18) - Production Systems (Alan Wagner)
  14. Lecture 14 (9/20) - Expert Systems (Mitch Parry)
  15. Lecture 15 (9/23)
  16. Lecture 16 (9/25)
  17. Lecture 17 (9/27) - Search-Based Planning and Planning as Satisfiability (Zsolt Kira)
  18. Lecture 18 (9/30) - Knowledge Structures (Chip Mappus)
  19. Lecture 19 (10/2) - Knowledge Structures (Phillip Jones)
  20. Lecture 20 (10/4) - Knowledge Structures (Chip Mappus)
  21. Lecture 21 (10/7) - Truth Maintenance Systems and Constraint Propogation (Carl Cox)
  22. Lecture 22 (10/9)
  23. Lecture 23 (10/16) - Knowledge-Based Reasoning and Learning (Stephan Urbanski)
  24. Lecture 24 (10/18) - Learning (Anuj P. Shah)
  25. Lecture 25 (10/21) - Learning (Bart Presnell)
  26. Lecture 26 (10/23) - Probability (Mitch Parry)
  27. Lecture 27 (10/25)
  28. Lecture 28 (10/28)
  29. Lecture 29 (10/30)
  30. Lecture 30 (11/1)
  31. Lecture 31 (11/4)
  32. Lecture 32 (11/6)
  33. Lecture 33 (11/8) - Input and Output as part of Intelligence (Andreas Lachenmann)
  34. Lecture 34 (11/11) - Semantic Analysis (Mitch Parry)
  35. Lecture 35 (11/13) - Vision (Logan Hauenstein)
  36. Lecture 36 (11/15)

Last modified: Tue Dec 3 15:26:51 EST 2002