The aim of this thesis is to evaluate the use of Search-based Procedural Content generation (SBPCG) to help a designer create levels for different game styles. I show how SBPCG can be used for level generation in different game genres by surveying both paper and released commercial solutions. I then provide empirical data by using a Genetic Algorithm (GA) to evolve levels in two different game types, first one being a space puzzle game, and the second a platform game. Constraints from a level designer provide a base to create fitness functions for both games with success. Even though difficulties with level representation make it hard for a designer to work with this technique directly, the generated levels show that the technique has promising potential to aid level designers with their work.
Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:liu-102212 |
Date | January 2013 |
Creators | Lundgren, Jesper |
Publisher | Linköpings universitet, Institutionen för datavetenskap, Linköpings universitet, Tekniska högskolan |
Source Sets | DiVA Archive at Upsalla University |
Language | English |
Detected Language | English |
Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
Format | application/pdf |
Rights | info:eu-repo/semantics/openAccess |
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