CS 151 - Artificial Intelligence

Department of Computer Science
Pomona College CS 151 - Artificial Intelligence
Fall 2010

instructor: Dave Kauchak
e-mail: [first_initial][last_name]@cs.pomona.edu
office hours: Edmunds 221
Mon. 4-5pm, Tue. 10:30am-12 and Th. 10am-11
and by appointment

TAs: Dandre Allison and Joel Detweiler
office hours: Edmunds 229
Mon. 7-9pm and Tue. 7-9pm

time: M/W 2:45-4pm
location: Edmunds 114
web page: http://www.cs.pomona.edu/classes/cs151/

textbook:

Artificial Intelligence: A Modern Approach (Third Edition). 2010. Stuart Russel and Peter Norvig, Peter. Prentice Hall, New Jersey.
** Make sure you get the third edition, which just came out and has a number of additions and updates from the second edition, which came out in 2003.

assignment submission: How to submit assignments

administrivia

Announcements

No class on Wednesday 11/24
The due date for the first project status report is moved to 11/17 (originally 11/15)
Assignment 5 is available (starter code). Due Wednesday 11/10 at midnight.
Final project details are available.
Final project literature review is available. Due Friday 10/29 at 6pm
If anyone is having problems getting the files for assignment 4, I've also posted them here
Assignment 4 is available. Due Wednesday, 10/20 at midnight.
Assignment 3 is available. Due Monday, 10/4 at the beginning of class, in class.
I've extended the due date for Assignment 2 to Friday, 9/24 at 5pm.
Assignment 2 with starter code is available. Due Wednesday, 9/22 at 2:44pm.
Assignment 1 is available. Due Wednesday, 9/8 at 2:44pm

Schedule

Note: This is a very tentative schedule and is subject to change

Date	Topic	Reading	Problems	Comments
9/1	intro, Python (pdf) - examples	Ch. 1, 2.1-2.3
9/6	uninformed search (pdf)	Ch. 3.1-3.4	written 1 (solution)	To be done by 9/13
9/8	informed search (pdf)	Ch. 3.5-3.6
9/13	adversarial search (pdf) - AB example	Ch. 5.1-5.3	written 2 (solution)	To be done by 9/20
9/15	game playing conclusions (pdf)	Ch. 5.4-5.9
9/20	Local search (pdf)	Ch. 4.1-4.2	written 3 (solutions)
9/22	CSPs (pdf)	Ch. 6
9/27	probability (pdf)	Ch. 13 (Optional: Appendix A.3)	written 4 (solution)
9/29	more prob (pdf), mancala tournament	Ch. 14.1-14.4
10/4	bayesian (pdf)	Ch. 14.5, 14.7
10/6	bayesian (pdf)	Ch. 18.1-18.2, 20.1-20.2.2, popular media article	written 5 (solution)
10/11	bayesian/review (pdf)	NB text classification
10/13	Exam 1
10/18	Fall break
10/20	HMMs (pdf)	Ch. 15.1-15.3	written 6 (solution)
10/25	HMMs (pdf)	Ch. 15.5
10/27	machine learning (pdf)	Ch. 18.1-18.3
11/1	machine learning (pdf)	Ch. 18.8-18.9, Ch. 15, first subsection	written 7 (solution)
11/3	machine learning (pdf)	Ch. 20.3
11/8	neural nets (pdf)	Ch. 18.6-18.7
11/10	knowledge representation (pdf)	Ch 7.4, 8.1-8.2, 12.1 Optional: NELL paper
11/15	natural language processing (pdf)	Ch. 23.4, 22.1	written 8 (solution)
11/17	natural langauge processing (pdf)	Ch. 23.1-2		Status report 1 due
11/22	computer vision (pdf)	Ch. 24.1-24.3	written 9 (soution)
11/24	NO CLASS
11/29	robotics/review (pdf)	Ch 25.1-25.2, 25.8-25.9		Status report 2 due
12/1	Exam 2
12/6	philosophy of AI (pdf)	Ch. 26
12/8	ethics of AI (pdf)

Final exam (presentations!) on Wednesday, Dec. 15 at 2:00pm.

Resources

Python
The Python documentation, at the official Python website. The tutorial, linked from the documentation pages, is particularly helpful.
Other (to appear soon)