Evolutionary Algorithms and Game AI

Simon Lucas / Queen Mary University of London

Mar 29, 2021

Abstract: Evolutionary algorithms are powerful black-box optimisers that find many applications in Game AI. They can be applied in real-time to provide robust policies across a range of games, or at design time for procedural content generation or game parameter tuning. I’ll outline the key concepts, give some insights into why they often work surprisingly well, and discuss future directions.

Bio: Simon Lucas is a professor of Artificial Intelligence and Head of the School of Electronic Engineering and Computer Science at Queen Mary University of London where he also heads the Game AI Research Group. He holds a PhD degree (1991) in Electronics and Computer Science from the University of Southampton. He is the founding Editor-in-Chief of the IEEE Transactions on Games and co-founded the IEEE Conference on Conference on Games. His research involves simulation-based AI and evolutionary algorithms applied to Game AI, and work towards Artificial General Intelligence. He is a fellow of the Alan Turing Institute, and a visiting researcher at Facebook