Computational Intelligence in Games
Description of the course
This course addresses the basic and advanced topics in computational intelligence and games. This course has three parts:
Part one addresses the basics of Evolutionary Game Theory (EGT). In this part, you will learn about simple games such as scissors/rock/paper and the main focus on the strategies for playing games.
Part two is about learning agents, and we focus on reinforcement learning mechanisms. There are three questions for games:
Part three contains the advanced topics in games and artificial intelligence, such as how can we program an agent who can pass a Turing test? how can we consider physical constraints of a spaceship while moving in an unknown terrain? etc.
This course will be held in English and is for Bachelor (5CP) and Master (6CP: including extra programming assignment) students.
Lectures and Tutorials
- Sanaz Mostaghim (Lectures)
- Sebastian Mai (Tutorials)
- Carlo Nübel (Tutorials)
Lectures take place on Tuesdays 13:00 - 14:30 in Room G02-311
Slides
Recorded lectures are on Mediasite: /OVGU/Fakultäten/Informatik (FIN)/Institut für Intelligente Kooperierende Systeme (IKS)/AG Computational Intelligence/Computational Intelligence in Games
Please note that you need to use your URZ account to get access to the recordings.
Exercises
Exercises take place on Wednesdays 13:00 to 15:00 in G22A-020. During the exercise, you will solve assignments at home and present your solutions during exercise classes. In addition, you will participate in an AI competition, where you will program an AI that can play a game.
This year, the competition is based on the VGC AI Competition. If your AI performs well during the course, we encourage you to participate in the international competition, which is hosted at the IEEE Conference on Games 2024.
Date | Exercise Sheet | Materials | Solution |
10.04. | No Exercise | ||
17.04. | Introduction AI Competition | AI Competition | |
24.04. | Sheet 1 | Sheet 1 Code | Sheet 1 solution |
01.05. | No Exercise | ||
08.05. | Sheet 2 | ||
15.05. | Sheet 2 + Q&A | Sheet 2 Code | Sheet 2 solution |
22.05. | Sheet 3 | Sheet 3 Code | Sheet 3 solution |
27.05. | Submission for Intermediate Competition | ||
29.05. | Intermediate Competition, Q&A | ||
05.06. | Sheet 4 | Sheet 4 Code | Sheet 4 solution |
12.06 | Q&A | ||
19.06. | Sheet 5 | Sheet 5 Code | Sheet 5 solution |
26.06. | Q&A | ||
03.07. | Sheet 6 | Sheet 6 | Sheet 6 solution |
08.07. | Final Submission for AI Competition | ||
10.07. | Game AI Competition |
Past Exams:
Literature
- Yannakakis, Georgios N., and Julian Togelius. Artificial Intelligence and Games. Springer, 2018. --> Link
- Richard S. Sutton and Andrew G. Barto, Reinforcement Learning: An Introduction, MIT Press, Cambridge, MA, 1998 --> Link
- Nowak, Martin, Evolutionary dynamics : exploring the equations of life, Cambridge, Mass. [u.a.] : Belknap Press of Harvard Univ. Press , 2006 --> Link to OvGU Library
- Ian Millington and John Funge, Artificial Intelligence for Games, CRC Press, 2009
- T. L. Vincent and J. L. Brown, Evolutionary Game Theory, Natural Selection and Darwinian Dynamics, Cambridge University Press, 2012
- Jorgen W. Weibull, Evolutionary Game Theory, MIT Press, 1997
- Thomas Vincent, Evolutionary Game Theory, Natural Selection, and Darwinian Dynamics, Cambridge University Press, 2005
- Josef Hofbauer, Karl Sigmund, Evolutionary Games and Population Dynamics, Cambridge University Press, 1998
- Kalyanmoy Deb, Multi-Objective Optimization using Evolutionary Algorithms, Wiley, 2001
- Literature about PCG: Paper1, Paper2, Paper3, Paper4
- Kruse, Borgelt, Klawonn, Moewes, Ruß, Steinbrecher, Computational Intelligence, Vieweg+Teubner, Wiesbaden, 2011
- Ines Gerdes, Frank Klawonn, Rudolf Kruse, Evolutionäre Algorithmen, Vieweg, Wiesbaden, 2004
- Zbigniew Michalewicz, Genetic Algorithms + Data Structures = Evolution Programs. Springer, Berlin, 1998