Instructor: Lenhart K. Schubert
Office Hours: Tuesdays and Thursdays 3:30-4:30pm or by appointment
Office: CSB 733
Extension: 5-8845
e-mail: schubert"at"cs etc.
TA: David Ahn
Office hours: M 5:00-6:00, TR 11:00-12:00 (CSB 626)
Recitations (beginning Jan 23): F 2:00-3:00 (CSB 601)
e-mail:davidahn@cs.rochester.edu
You should read the text assignment or handout before coming to class.
| Week | Date | Topic | Subtopic | Reading |
|---|---|---|---|---|
| 1 | 15 Jan | Artificial Intelligence |
1: Meaning, goals and foundations of AI | Ch 1 (skim 2) |
| 2 | 20 Jan 22 Jan | LISP |
2: Basic LISP programming 3: Lambda, iteration, etc. | Wilensky |
| 3 | 27 Jan 29 Jan | Search |
4: State space search, A* 5: Problem reduction | Ch 3, 4(4.1-4.2) |
| 4 | 3 Feb 5 Feb | Game Playing |
6: Minimax, alpha-beta 7: chance; state of the art | Ch 5 |
| 5 | 10 Feb 12 Feb | Logic & Reasoning |
8: Propositional logic 9: Predicate logic | Ch 6, 7 (7.1, 7.3) |
| 6 | 17 Feb 19 Feb | Resolution |
10: Clause form 11: Resolution | Ch 9 (9.6) |
| 7 | 24 Feb 26 Feb | Knowledge Representation |
12: Hierarchies, rules 13: Nets, frames | Ch 8 (8.1-8.4) Ch 10 (10.6-10.7) |
| 8 | 3 Mar 5 Mar | Planning |
14: STRIPS 15: Partial-order planning | Handout Ch 11 (11.5-11.7) |
| 10 Mar 12 Mar | Spring Break | |||
| 9 | 17 Mar 19 Mar | Probabilistic Reasoning |
16: Basics 17: Using Bayes' rule | Ch 14 |
| 10 | 24 Mar 26 Mar | Bayes Nets |
18: Net structure 19: Inference | 15 (15.1-15.3) |
| 11 | 31 Mar 2 Apr | Learning to Classify |
20: Decision trees 21: Neural nets | Ch 18 (18.1-18.3) Ch 19 (19.1-19.5) |
| 12 | 7 Apr 9 Apr | Reinforcement Learning |
22: Markov processes 23: Q-learning | Handout Ch 20 |
| 13 | 14 Apr 16 Apr | Natural Language |
24: Grammars and parsing 25: Semantic interpretation | Ch 22, 23 (23.2) |
| 14 | 21 Apr 23 Apr | Vision |
26: Early vision 27: Labels, objects | Ch 24 |
| 15 | 28 Apr | Robotics |
28: sensors, effectors, motion, navigation | Ch 25 |