Announcements

Syllabus

Class policies

Schedule

Resources

Course Schedule

B351/Q351 Fall 2013

 

(subject to change)

 

No.

Date

 

Subject

Out

In

Readings

1

27-Aug

Tu

Class overview, intro to AI

 

 

R&N 1,26

2

29-Aug

Th

Search

HW1

 

R&N 3.1-3

3

3-Sep

Tu

Search, pt 2

 

 

R&N 3.4

4

5-Sep

Th

Heuristic search

 

 

R&N 3.5

5

10-Sep

Tu

Beyond classical search

 

 

R&N 4.1-5

6

12-Sep

Th

Game playing

HW2

HW1

R&N 5.1-4

7

17-Sep

Tu

Alpha-Beta pruning, stochastic games

 

 

R&N 5.5-6

8

19-Sep

Th

Constraint satisfaction problems

 

 

R&N 6.1-3

9

24-Sep

Tu

Constraint satisfaction problems, pt 2

 

 

R&N 6.4-5

10

26-Sep

Th

Homework review

HW3

HW2

 

11

1-Oct

Tu

Introduction to Uncertainty

 

 

R&N 4.3-4,13.1-2

12

3-Oct

Th

Probabilistic inference

 

 

R&N 13.3-6

13

8-Oct

Tu

Bayesian Networks

 

 

R&N 14.1-3

14

10-Oct

Th

Midterm review

 

HW3

 

15

15-Oct

Tu

Midterm

 

 

16

17-Oct

Th

Bayesian networks, pt 2

 

 

R&N 14.4-5

17

22-Oct

Tu

Learning probabilistic models

 

18

24-Oct

Th

Statistical learning

HW4

R&N 20.1-2

19

29-Oct

Tu

Intro to machine learning

R&N 18.1-2

20

31-Oct

Th

Decision tree learning

 

R&N 18.3,10

21

5-Nov

Tu

Neural networks

R&N 18.6-7

22

7-Nov

Th

Guest lecture: Statistical relational learning

HW5

HW4

23

12-Nov

Tu

Support vector machines, nonparametric learning

R&N 18.8-9

24

14-Nov

Th

Evaluating learning

 

 

R&N 18.4-5

25

19-Nov

Tu

Intelligent agents

R&N 2

26

21-Nov

Th

Planning under uncertainty

HW6

HW5

R&N 17.1-4

--

26-Nov

Tu

 

 

--

28-Nov

Th

 

 

 

27

3-Dec

Tu

Reinforcement learning

 

R&N 21.1-4

28

5-Dec

Th

Robotics and motion planning

 

29

10-Dec

Tu

Computer vision

 

 

30

12-Dec

Th

Review

 

HW6

19-Dec

Th

Final Exam, 12:30-2:30pm

 

 

HW1. Uninformed search and heuristic search.

HW2. Minimax search for the Gobblet game.

HW3. CSPs and probability warmup.

HW4. Probabilistic inference and Bayesian networks.

HW5. Machine learning for text classification.

HW6. Evaluating intelligent agents