CSC 290: Artificial Intelligence (Spring 2007)

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Course Description: This is a restructuring of the old Artificial Intelligence course in two directions. First, it has as a prerequisite just one course in programming (CS-I or its equivalent), to make it accessible to non-CS majors and much earlier in the curriculum. Second, it places special emphasis on evolutionary programming. The course covers five topics: search and games, language understanding, neural networks, genetic algorithms and evolutionary programming, and artificial life.

InstructorJoseph O'Rourke
Credits:  4
Latin Honors Designation:  M (Math)
Location:Burton B02 for all classes.
Enrollment: No limit. 8 pre-enrolled.
Meeting Times: We meet two times a week; there is no lab, although we will do several "minilabs" during class time.


Prerequisites: CSC 111 (Computer Science I) or equivalent; MTH 111 (Calculus I) or MTH 153 (Discrete) or equivalent. We need both programming experience and some mathematical sophistication, but I will not assume either extensive programming experience or advanced mathematical knowledge. If you are worried about the pre
Programming Language: I am assuming only exposure to Python from Computer Science I. Programming experience in C or C++ is not required. One-course experience in C++ or Java will suffice to supplant experience with Python. We will use two other languages that I will assume are new to everyone: LISP, and breve/steve.
Textbook: None!  This course is somewhat unusual and is not approximated by any existing textbook. This saves you money but puts a demand on your attendance, attention, and note-taking.
Assignments:  There will be 6 assignments, rougly one every other week. Some of the assignments will involve short presentations to the class. Assignments will be due (generally) Thursday mornings at 8:00AM. Collaboration is permitted, even encouraged, on assignments. See also Late Policy and Resubmission Policy.
Take-Home Final: There will be a take-home final exam, available by the last day of classes, 2 May, and due back at the end of the exam period, 11 May.
Presentation: Each student will be responsible for exploring a topic in AI of their choice, and sometime during the semester (a time of their chosing), giving a 15-minute presentation to the class on the topic, supported by a Web page of references and links.
Assignments 70%
Presentation 10%
Take-home Final 20%
See Grading Numerology for my grading system.


O'Rourke Office Hours & Schedule