Evolutionary Machine Learning and Games
It provides a comprehensive overview for researchers in AI and games, but is incremental as it synthesizes existing work rather than presenting new findings.
This chapter surveys the application of evolutionary machine learning (EML) to games, covering areas such as playing games, generating content, and modeling players, and structures the discussion based on whether evolution augments machine learning or vice versa.
Evolutionary machine learning (EML) has been applied to games in multiple ways, and for multiple different purposes. Importantly, AI research in games is not only about playing games; it is also about generating game content, modeling players, and many other applications. Many of these applications pose interesting problems for EML. We will structure this chapter on EML for games based on whether evolution is used to augment machine learning (ML) or ML is used to augment evolution. For completeness, we also briefly discuss the usage of ML and evolution separately in games.