Spring 2010 CAP 4053 AI for Game Programming: Syllabus
MW 9:30AM - 10:45AM in COMM room 116
Instructor: Dr. Kenneth Stanley
EPlex Research Group: http://eplex.cs.ucf.edu
Office: Harris 332
Office Hours (starting 1/11/10): Mondays 11am-12pm and Tuesdays 3-4pm
TA: Derick Janssen
TA Office: HEC 308 "The Cave"
TA Office Hours: MW 1:30-2:30
Derick's email: email@example.com
Link to Homework Assignments and Lectures
Programming Game AI by Example by Mat Buckland, Wordware Publishing, Inc. (2004)
AI Techniques for Game Programming by Mat Buckland, Course Technology PTR (2002)
Software and Source CodeDemo code for Programming Game AI by Example is available at http://www.wordware.com/files/ai. The "Buckland" files contain the code.
Any version of NEAT can be used for the class homework assignmentsts. A number of versions are available here: http://www.cs.ucf.edu/~kstanley/#software
The latest clean version written by myself is rtNEAT, available here. A stripped down version of my non-real-time code is neatVS.zip, refitted for easy compiling by Jared Johnson..
OverviewThe video game industry is a major consumer of artificial intelligence (AI) technology. It is one of the few areas of computer science wherein regular consumers routinely interact with cutting edge techniques. Video game consumers are demanding AI innovation to make games more interesting and fun. The course introduces a broad range of AI techniques for games, contrasting recent cutting-edge approaches with more traditional ones. Both video games and turn-based games (i.e. board games) are covered from a variety of perspectives. Topics range from standard techniques such as scripting and path-finding to recent innovations like reinforcement learning and real-time neuroevolution. Industry needs and priorities are also addressed. The course focuses on practical application and hands-on experience, culminating in a final project. Thus, students will leave equipped to apply the latest approaches to real games.
Grading PolicyThree project-based homework assignments (60% of grade)
- Foundations: Create a simple experimental platform with agents and sensors (with partner)
- Algorithms: Implement pathfinding and evolution in platform (individual)
- Final Project: Convert it into a simple game (with partner from first assignment)
Two exams testing comprehensive knowledge (40% of grade)
- Midterm: Foundations and early algorithms
- Final: Comprehensive
Late assignments lose 10% the first day late, 40% the second, and are not accepted after that.
CheatingAll of the work that you turn in or present must be your own. Cheating, plagiarism, and any other form of academic dishonesty will be penalized. The minimum penalty for cheating will include:
- An automatic zero on the assignment -- this grade may not be dropped; and
- reduction of your final grade by one letter grade; and
- notification of the incident to the UCF Office of Student Conduct.
Plagiarism and paraphrasing are forms of cheating. Plagiarism is the presentation of others' ideas and writings as your own. Paraphrasing is taking someone else's sentence, changing a few words, and then presenting it as your own. Both are unacceptable in this class.
Important Students may not turn in code from either of Mat Buckland's book with the exception of Mat Buckland's NEAT, engine code (i.e. code not specifying AI algorithms), or otherwise specified by Dr. Stanley. Turning in book code will be penalized as plagiarism.
ScheduleJanuary 11 Class introduction, AI & the Video Game Industry
January 13 Game Engines for AI
January 18 No class: Martin Luther King Jr. Day
January 20 Mathematical Foundations
January 25 The Perception and Action Loop
January 27 Sensor Computations
February 1 Internal State, Finite State Machines, and Scripting
February 3 Pathfinding and Search
February 8 Advanced Pathfinding, Board Games and Game Tree Search
February 10 Neural Networks and Backpropagation
February 15 Evolutionary Computation
February 17 Evolutionary Computation 2
February 22 Neuroevolution
February 24 Midterm
March 1 NeuroEvolution of Augmenting Topologies (NEAT)
March 3 Real-time Neuroevolution and NeuroEvolving Robotic Operatives (NERO)
March 8 No class: Spring break
March 10 No class: Spring break
March 15 More NERO
March 17 Coevolution and multiagent learning
March 22 Project Discussion and Game Design Issues
March 24 Coordinate Systems, Perspectives, and Control; Mitigating Computational Complexity
March 29 Game proposals 1
March 31 Game proposals 2
April 5 Interactive Evolution and AI for Content Generation, AI in Multiplayer Games and Massive Multiplayer Online Worlds
April 7 Game Industry Perspectives
April 12 Galactic Arms Race : Online Multiplayer Automated Content Evolution from UCF
April 14 Artificial Life
April 19 Final Exam in Class
April 21 TBD
April 26 Presentations
Final: April 30th
7am-9:50am - Presentations Continue Complete Finals Schedule