Course Schedule

B551 Fall 2009

Note: to print slides for lectures 1-3 black on white, choose the grayscale printing option in Powerpoint.

(subject to change)

No.	Date		Subject	Out	In	Readings
1	1-Sep	Tu	Class overview, intro to AI			R&N 1,26
2	3-Sep	Th	Agents and problem solving			R&N 2
3	8-Sep	Tu	Search	HW1		R&N 3.1-3
4	10-Sep	Th	Search, pt 2			R&N 3.4-5
5	15-Sep	Tu	Heuristic and local search			R&N 4.1-5
6	17-Sep	Th	Real-world search applications		HW1
7	22-Sep	Tu	Guest lecture, David Leake	HW2
8	24-Sep	Th	Constraint satisfaction problems			R&N 5.1-2
9	29-Sep	Tu	Constraint satisfaction problems, pt 2			R&N 5.3-4
10	1-Oct	Th	Game playing			R&N 6.1-7
11	6-Oct	Tu	Planning	HW3	HW2	R&N 11.1-4
12	8-Oct	Th	Motion planning			R&N 12.1
13	13-Oct	Tu	Guest lecture, Mike Gasser	HW4	HW3
14	15-Oct	Th	Introduction to uncertainty			R&N 12.3-6
15	20-Oct	Tu	Planning with uncertainty			R&N 13.1-4
16	22-Oct	Th	Planning with uncertainty, pt 2			R&N 17.1-4
17	27-Oct	Tu	Probabilistic inference			R&N 13.4-6
18	29-Oct	Th	Bayesian Networks	HW5	HW4	R&N 14.1-6
19	3-Nov	Tu	Probabilistic temporal models			R&N 15
20	5-Nov	Th	Statistical learning		HW5	R&N 20.1-3
21	10-Nov	Tu	Introduction to machine learning	HW6		R&N 18.1-2
22	12-Nov	Th	Decision tree learning			R&N 18.3
23	17-Nov	Tu	Neural networks	HW7	HW6	R&N 20.5
24	19-Nov	Th	Support vector machines			R&N 20.6
25	24-Nov	Tu	Review
---	26-Nov	Th	No class
26	1-Dec	Tu	Final project presentations		HW7
27	3-Dec	Th	Review, AI’s future		Final project report