Abstract Forward Models for Modern Games

Welcome to the website of the Abstract Forward Models for Modern Games project. This is an UK EPSRC funded project that aims to investigate how modern Statistical Forward Planning algorithms can be used in complex games. Statistical Forward Planning (SFP) techniques, such as Monte Carlo Tree Search (MCTS) or Rolling Horizon Evolutionary Algorithms (RHEA), have recently achieved remarkable performance in games research. This project addresses the main reasons behind the small uptake of SFP methods in the games industry: the lack of fast and reliable Forward Models (FM) that can be abstracted for its use by SFP algorithms in modern video-games.