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Artificial Intelligence Syllabus
CMPS 356 - Winter 2008
Dr. Melissa Danforth

Office: Sci 403, 654-3180 
Office Hours: MWF 3:30pm - 5:10pm or by appointment
Email: melissa@cs.csubak.edu
Course web site: http://www.cs.csubak.edu/~mdanfor/
Course meets MWF 11:00am - 12:25pm in Sci 414,
             Tu  10:30am - 12:55pm in Sci 414

Course Description:
This course is intended to teach the fundamentals of artificial 
intelligence which include topics such as expert systems, artificial 
neural networks, fuzzy logic, inductive learning and evolutionary algorithms.
More course information can be found at the official department course
description webpage:
http://www.cs.csub.edu/newsite/CS/CourseDescription/356_Description_v1.htm

Prerequisite:
CMPS 223

Textbook: 
Artificial Intelligence: A Guide to Intelligent Systems, 2nd edition.
Michael Negnevitsky. Addison-Wesley, 2005.  ISBN: 0-321-20466-2.

Topics:
Chapter 1	Introduction to knowledge-based intelligent systems
Chapter 2	Rule-based expert systems
Chapter 3	Uncertainity management in rule-based expert systems
Chapter 4	Fuzzy expert systems
Chapter 5	Frame-based expert systems
Chapter 6	Artificial neural networks
Chapter 7	Evolutionary computation
Chapter 8	Hybrid intelligent systems
Chapter 9	Knowledge engineering and data mining

Attendance:
Students are responsible for their own attendance. The topics covered
in lecture will be listed on the course website. Lab attendance is not 
required but is strongly encouraged.

Academic Integrity Policy: 
Assignments may discussed in groups. If the assignment is a group 
assignment, the group turns in one assignment for the entire group. 
However, if the assignment is an individual assignment, each student 
must turn in their own work; no direct copying is allowed. You may 
discuss individual assignments with other students, but you must write 
up the assignment in your own words.  Refer to the Academic Integrity 
policy in the campus catalog.

Computer Lab:
The computer lab in Sci 409 is available for use by students in this 
course outside of class time on a first come, first serve basis.

Grading:	Labs/Homework	30%
		Midterms(2)	40% (20% for each Midterm)
		Final		30%

Homework/Lab Policy: 
Homeworks and labs may be worked on and discussed in groups, but every 
student must turn in their own assignments in their own words. Refer to
the Academic Integrity Policy above. Assignments will be posted online 
on the course website. The due date will be given with the assignment.
Late labs are not accepted, however partial credit will be given for
incomplete labs. Late homework is accepted, but it will be marked down 
10% for every day it is late. Homework assignments more than three days 
late will not be accepted. Saturday and Sunday count as one day under 
this policy.

Homework/Lab Submission:
Assignments are submitted by emailing the instructor from the Computer 
Science department server or by turning in a hardcopy of the assignment
to the instructor. If emailing, all files must be in text or PDF format.
Do not use RunnerMail or any other email method. If you believe you 
submitted the assignment on time but the instructor has not received it, 
contact the instructor.

Midterms:
Midterm 1 will be Tuesday January 29, 2008 during the lab time block.
Midterm 2 will be Tuesday February 19, 2008 during the lab time block.

Makeup midterms will not be given, but the other midterm will be counted 
proportionally higher if you have a valid reason for missing a midterm. 

Final:
Wednesday March 12, 2008 from 11:00am - 1:30pm in Sci 414