Learning Finite State Machines with Gameplay Video

Abstract

There has been an ongoing trend of pitching neural networks as playable game engines. However, from a game developer’s perspective, world models are not very practical since they cannot make changes like in a traditional game engine. Our project learns a model of pacman from gameplay video that can be played in pygame. The learnt model captures the original behaviour of the entities in the majority of the instances.