Abstract
This tutorial introduces several techniques and application areas for computational intelligence in games, such as board games and video games. We will give a broad overview of the use cases and popular methods for computational intelligence in games, and in particular cover the use of computational intelligence for learning policies (e.g., evolutionary reinforcement learning using neuroevolution), planning (e.g., rolling horizon and online planning), and designing (search-based procedural content generation, procedural content generation via reinforcement learning and experience driven procedural content generation). The recent advances of LLMs and games will also be covered. The basic principles will be explained and illustrated by examples from our own research as well as others' research.
Duration: 2 hours
Outline
- Introduction: who are we, what are we talking about?
- Why do research on computational intelligence and games?
- Part 1: Playing games
- Reasons for building game-playing AI
- Characteristics of games (and how they affect game-playing algorithms)
- Reinforcement learning through evolution
- Neuroevolution
- Planning with evolution
- Part 2: Designing and developing games
- The need for AI in game design and development
- Procedural content generation
- Search-based procedural content generation
- Procedural content generation machine learning (PCGML)
- Procedural content generation via reinforcement learning (PCGRL)
- Experience driven procedural content generation (EDPCG)
- Part 3: LLMs and Games
- LLMs for playing games
- LLMs for designing games
- Ethical consideration of LLMs in games
Presenters
Presenters’ Bios
Jialin Liu is currently an Associate Professor at the School of Data Science of Lingnan University, Hong Kong SAR, China. She received her Ph.D. from the Université Paris-Saclay in 2016, M.Sc. degree from the École Polytechnique and the Université Paris-Sud in 2013, Diplôme d'Ingénieur from the Polytech'Paris-Sud in 2012, and B.E. degree from the Huazhong University of Science and Technology in 2010. Her research interests include artificial intelligence in games, evolutionary computation, and fair machine learning. She is an Associate Editor of IEEE Transactions on Evolutionary Computation, IEEE Transactions on Artificial Intelligence, IEEE Transactions on Games and Knowledge-Based Systems.
Julian Togelius received the B.A. degree from Lund University, Lund, Sweden, in 2002, the M.Sc. degree from the University of Sussex, Brighton, U.K., in 2003, and the Ph.D. degree from the University of Essex, Colchester, U.K., in 2007. He has worked at IDSIA, Lugano, Switzerland, and the IT University of Copenhagen, Copenhagen, Denmark. He is currently an Associate Professor of Computer Science and Engineering at New York University and a co-founder of modl.ai. He works on artificial intelligence for games and on games for artificial intelligence. Julian was the former Editor-in-Chief of IEEE Transactions on Games. He is an IEEE Fellow.
Georgios N. Yannakakis is a Professor at the Institute of Digital Games, University of Malta, and a co-founder of modl.ai. He does research at the crossroads of artificial intelligence, computational creativity, affective computing, advanced game technology, and human–computer interaction. He has published more than 400 papers in the aforementioned fields, and his work has been cited broadly. Prof. Yannakakis is the Editor-in-Chief of IEEE Transactions on Games and an Associate Editor of IEEE Transactions on Evolutionary Computation. He is an IEEE Fellow.