{"type":"ScholarlyArticle","title":"Player Movement Models for Video Game Level Generation","authors":[{"name":"Sam Snodgrass","slug":"sam-snodgrass","given":"Sam","family":"Snodgrass","affiliation":"Department of Computer Science , Drexel University Philadelphia , PA USA"},{"name":"Santiago Ontañón","slug":"santiago-ontanon","given":"Santiago","family":"Ontañón","affiliation":"Department of Computer Science , Drexel University Philadelphia , PA USA"}],"abstract":"The use of statistical and machine learning approaches, such as Markov chains, for procedural content generation (PCG) has been growing in recent years in the field of Game AI. However, there has been little work in learning to generate content, specifically levels, accounting for player movement within those levels. We are interested in extracting player models automatically from play traces and using those learned models, paired with a machine learning-based generator to create levels that allow the same types of movements observed in the play traces. We test our approach by generating levels for Super Mario Bros. We compare our results against the original levels, a previous constrained sampling approach, and a previous approach that learned a combined player and level model.","doi":"10.24963/ijcai.2017/105","url":"https://ijcai.org/proceedings/2017/105","pdf":"https://ijcai.org/proceedings/2017/0105.pdf","markdown":"https://ijcai.org/proceedings/2017/105.md","bibtex":"https://ijcai.org/proceedings/2017/bibtex/105","volume":{"slug":"2017","title":"Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2017","url":"https://ijcai.org/proceedings/2017/","year":2017,"location":"Melbourne, Australia","dates":"19-25 August 2017","editors":"Carles Sierra","isbn":"978-0-9992411-0-3","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2017"},"section":"Constraints and Satisfiability","track":"Main track","number":105,"pages":{"first":757,"last":763},"keywords":["Machine Learning: Machine Learning","Constraints and Satisfiability: Constraint Satisfaction","Multidisciplinary Topics and Applications: Computer Games"],"videos":[],"references":[{"position":1,"raw":"[Cenkner et al., 2011] Andrew Cenkner, Vadim Bulitko, and Marcia Spetch. 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