This course delves into the use of artificial intelligence in interactive environments. These environments range from the entertaining nature of role-playing games to more serious military simulations. In all these environments, agents and groups of agents must interact in an intelligent manner. Topics will include advanced pathfinding algorithms, sensory systems, group tactical strategies, and learning algorithms. Projects are an inherent part of the course.
Instructor: Jessica D. Bayliss
Office: bldg. 70, room 2511
Email: jdbics on rit.edu
Web Page: http://www.it.rit.edu/~jdb
Office hours: Please see my main web page.
Asking questions via email seems to work best for many people.
Monday/Wednesday, 4:00-5:50pm
Artificial Intelligence for Games by Ian Millington, Morgan Kaufmann, San Francisco, CA, 2006.
Course Web Page: http://www.it.rit.edu/~jdb/gameAI
I will distribute copies of other materials required for class. Information about reading and project assignments, exams, etc. will be linked from the course web page.
Programming Language Concepts (4003-450/4003-709)
Artificial Intelligence (4003-455/4005-750) or permission of the instructor
These prerequisites will be enforced.
Reading assignments will be given in class and may be expected to be completed by the next class time. Each written/coded homework assignment will be collected and graded. Written/coded homework assignments are posted at least 6 days before they are due and are due when stated in the assignment. The actual assignments will be available off of the course web page. Students may submit late, but a penalty of 10% per day will be assessed for up to one week. After one week, the assignment will not be accepted. As an example, and assignment due on Monday will receive a maximum grade of 90% if turned in on Tuesday and will receive no credit if turned in on or after the next Monday.
If stated in the homework/project, you may work on the assignment in groups of 1 or 2. If you choose to work as a group of 2, both of you should contribute significantly to the solution for every problem. You should submit only one copy of the homework with both of your names on it unless there is an individual portion of the homework assignment. You are not allowed to discuss the homework with anyone except your partner and me if you have a partner. You should submit only work that is completely your own and you should be able to explain all of your homework to me.
You will be required to analyze the AI in a game of your choice. This paper must be done individually. More information will be available on the course web site.
In order to aid you with learning the topics, some classes
will be spent in a lab setting. Most of your attendance and participation grade
will come from these activities. Occasionally, you may be asked to work in
groups in class or to discuss a class topic. The rest of your attendance and
participation grade will come from your participation in these activities.
There will be a midterm during the quarter. While the test will be closed book and notes, you may bring one sheet of letter-sized paper with your own hand-written notes.
A cumulative final exam will be given. Information on the final will be available from the course web page at least one week prior to the date of the final.
Exams cannot be made up except for real emergencies. If at all possible, you should contact me prior to the exam. Oversleeping, cars that don't start etc. do not constitute a valid excuse. If you lie to me or falsify documentation and I later find out about it, I will turn you in for academic dishonesty.
Approximately every 2 weeks you will be assigned an extra research paper to read. We will use 1 hour of the 2 hours of lab time in order to discuss this paper. All graduate students are expected to be able to adequately and in-depth explain what the paper is about as well as to analyze the paper. A written report of the paper may be required.
You may also be required to do extra activities in assignments.
50% Projects
20% Midterm
5% Participation and attendance
5% Game Analysis Paper
20% Final Exam
Numerical grades will be converted to letter grades according to the following scale:
> 90%: A; 80%-90%: B; 70%-80%: C; 60%-70%: D; < 60%: F.
Your final grade will never be more than one letter grade higher than your weighted average exam grade. In addition, if your weighted average exam grade is below 60%, you fail the course.
40% Projects
20% Midterm
5% Participation and attendance
10% Research papers
5% Game Analysis Paper
20% Final Exam
Numerical grades will be converted to letter grades according to the following scale:
> 90%: A; 80%-90%: B; 70%-80%: C; 60%-70%: D; < 60%: F.
Your final grade will never be more than one letter grade higher than your weighted average exam grade. In addition, if your weighted average exam grade is below 60%, you fail the course.
If you feel that an error was made in grading your project or exam, you have one week from the moment the graded work was handed back to dispute your grade.
The DCS Policy on Academic Dishonesty will be enforced.
You should only submit work that is completely your own. Failure to do so counts as academic dishonesty and so does being the source of such work. Submitting work that is in large part not completely your own work is a flagrant violation of basic ethical behavior and will be punished in accordance with the DCS Policy.