CS378 Computational Intelligence in Game Design I

Instructor:

Risto Miikkulainen
risto@cs.utexas.edu, (512) 471-9571
Office hrs: Wed 1:-1:30pm (details) & by appt.

TA:

Igor Karpov
ikarpov@cs.utexas.edu, (512) 471-9544
Office hrs: Thu 3:30-5pm, ENS 31NN

Mentors:

Yonatan Bisk
ybisk@cs.utexas.edu
Office hrs: Fridays 2-3pm, ENS 31NN
Homework evaluation hrs: Tue 1:30-3:30pm, ENS 31NN

Adam Dziuk
adziuk@cs.utexas.edu
Office hrs: Mondays 2-3pm, ENS 31NN
Homework evaluation hrs: Tue 6-8pm, ENS 31NN

Michael Fairley
comwiz@cs.utexas.edu
Office hrs: Mondays 11am-12pm, ENS 31NN
Homework evaluation hrs: Tue 12:30-1:30pm, 5-6pmENS 31NN

Description:

Interested in Game Programming or AI? UT's College of Natural Sciences will again this Spring offer a class focusing on the NERO video game (www.nerogame.org), an award-winning game AI project that has been featured on Slashdot, Games Digest, AAAI, KXAN, and numerous other venues. In this class, you will learn about different aspects of video game technology and will get hands-on experience in working with a real game engine. You will become familiar with cutting-edge AI research that may play a central role in the next generation of video games. The students work together in a team, exploring next-generation AI techniques as well as further developing NERO as an exciting game and as a valuable research platform for artificial intelligence.

There are no specific prerequisites, however you should be truly excited about working in some aspect of game technology and dedicated to making the team project a success.

Grading:

The class will be 3 credit hours. 75% of the grade is based on homework (each graded pass/fail), and 25% on a written project proposal (graded 0..100). Turning in the proposal or a homework late will reduce the grade 15% for the first 24hrs, 40% for the second, 75% for the third, and 100% after that. "Extra credit" on a homework is 15% (unless otherwise indicated in the assignment).

More details:

Class schedule
Presentations, demos, and readings
Other class resources

The NERO website
The NERO development wiki
The UTCS Neural Networks Research Group