Automatic Generation of Level Maps with the Do What’s Possible Representation

Daniel Ashlock, Christoph Salge

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Automatic generation of level maps is a popular form of automatic content generation. In this study, a recently developed technique employing the do what’s possible representation is used to create open-ended level maps. Generation of the map can continue indefinitely, yielding a highly scalable representation. A parameter study is performed to find good parameters for the evolutionary algorithm used to locate high quality map generators. Variations on the technique are presented, demonstrating its versatility, and an algorithmic variant is given that both improves performance and changes the character of maps located. The ability of the map to adapt to different regions where the map is permitted to occupy space are also tested.
Original languageEnglish
Title of host publication2019 IEEE Conference on Games (CoG)
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Number of pages8
ISBN (Print)978-1-7281-1885-7
Publication statusPublished - 23 Aug 2019
Event2019 IEEE Conference on Games (CoG) - London, UK
Duration: 20 Aug 201923 Aug 2019


Conference2019 IEEE Conference on Games (CoG)


  • Computer hacking
  • Sociology
  • Statistics
  • Automata
  • Evolutionary computation
  • Generators
  • Games


Dive into the research topics of 'Automatic Generation of Level Maps with the Do What’s Possible Representation'. Together they form a unique fingerprint.

Cite this