harnessing machine learning for procedural content generation in gaming: a comprehensive review

Procedural content generation (pcg) through automated and algorithmic content generation is an active research field in the gaming industry. recently, machine learning (ml) approaches have played a pivotal role in advancing this area. while recent studies have primarily focused on examining one or a few specific approaches in pcg, this paper provides a more comprehensive perspective by exploring a wider range of approaches, their applications, advantages, and disadvantages. furthermore, the current challenges and potential future trends in this field are discussed. although this paper does not aim to provide an exhaustive review of all existing research due to the rapid and expansive growth of this domain, it is based on the analysis of selected articles published between 2020 and 2024.