Controllable procedural map generation via multiobjective evolution
2013 (English)In: Genetic Programming and Evolvable Machines, ISSN 1389-2576, E-ISSN 1573-7632, Vol. 14, no 2, 245-277 p.Article in journal (Refereed) Published
his paper shows how multiobjective evolutionary algorithms can be used to procedurally generate complete and playable maps for real-time strategy (RTS) games. We devise heuristic objective functions that measure properties of maps that impact important aspects of gameplay experience. To show the generality of our approach, we design two different evolvable map representations, one for an imaginary generic strategy game based on heightmaps, and one for the classic RTS game StarCraft. The effect of combining tuples or triples of the objective functions are investigated in systematic experiments, in particular which of the objectives are partially conflicting. A selection of generated maps are visually evaluated by a population of skilled StarCraft players, confirming that most of our objectives correspond to perceived gameplay qualities. Our method could be used to completely automate in-game controlled map generation, enabling player-adaptive games, or as a design support tool for human designers.
Place, publisher, year, edition, pages
Springer , 2013. Vol. 14, no 2, 245-277 p.
Evolutionary computation, Multiobjective optimisation, Procedural content generation, Real-time strategy games, RTS, StarCraft
IdentifiersURN: urn:nbn:se:bth-6980DOI: 10.1007/s10710-012-9174-5ISI: 000317007700005Local ID: oai:bth.se:forskinfo8C4ABDD4960A5F3AC1257B5F00422598OAI: oai:DiVA.org:bth-6980DiVA: diva2:834543