Neuroevolution in Games: State of the Art and Open Challenges

Abstract

This paper surveys research on applying neuroevolution(NE) to games. In neuroevolution, artificial neural networksare trained through evolutionary algorithms, taking inspirationfrom the way biological brains evolved. We analyse theapplication of NE in games along five different axes, which are therole NE is chosen to play in a game, the different types of neuralnetworks used, the way these networks are evolved, how thefitness is determined and what type of input the network receives.The article also highlights important open research challenges inthe field