Decomposing the level generation problem with tiles

Search based procedural content generation uses search techniques to locate high-quality content elements for use in games. This study specifies and tests an evolutionary-computation based system to generate tiles and plans that decompose the problem of assembling large levels. Evolutionary computation is used as an off-line tool to generate libraries of both tiles and assembly plans. Systems for rapidly assembling tile libraries can then be used to generate large levels on demand with combinatorially huge numbers of levels available. The study also introduces new fitness functions, generalizing early work on checkpoint based fitness for the evolution of mazes, that is especially well suited for tile creation. Tiles are generated using two different representations that yield tiles with very different appearances. The study demonstrates assemblies of large levels and outlines several directions for extending the work.