20.500.12556/DiRROS-16292 Tools for landscape analysis of optimisation problems in Procedural Content Generation for games The term Procedural Content Generation (PCG) refers to the (semi-)automatic generation of game content by algorithmic means, and its methods are becoming increasingly popular in game-oriented research and industry. A special class of these methods, which is commonly known as search-based PCG, treats the given task as an optimisation problem. Such problems are predominantly tackled by evolutionary algorithms. We will demonstrate in this paper that obtaining more information about the defined optimisation problem can substantially improve our understanding of how to approach the generation of content. To do so, we present and discuss three efficient analysis tools, namely diagonal walks, the estimation of high-level properties, as well as problem similarity measures. We discuss the purpose of each of the considered methods in the context of PCG and provide guidelines for the interpretation of the results received. This way we aim to provide methods for the comparison of PCG approaches and eventually, increase the quality and practicality of generated content in industry. optimization search-based procedural content generation exploratory landscape analysis Mario level generation optimizacija postopkovno ustvarjanje vsebine z iskanjem raziskovalna analiza problemske pokrajine ustvarjanje nivojev igre Mario true false false Angleški jezik Slovenski jezik Neznano 2023-02-24 09:47:51 2023-02-24 09:47:53 2023-02-25 03:41:56 0000-00-00 00:00:00 2023 0 0 Nasl. z nasl. zaslona; Soavtorica iz Slovenije: Tea Tušar; Opis vira z dne 15. 2. 2023; str. 1-42 Vol. , [article] no. 110121 2023 0000-00-00 PostprintKoncna VTisku NiDoloceno 0000-00-00 0000-00-00 0000-00-00 004.9 1872-9681 10.1016/j.asoc.2023.110121 141799683 RAZ_Volz_Vanessa_2023.pdf RAZ_Volz_Vanessa_2023.pdf 1 3DFE985C37EB6D2D9FDBBBCF239DC417 285592a7e49ce04e88c3050c10ced0b461acd1437487bd10028df2bcba7a4ee8 9ed34883-b418-11ed-b359-001a4af901a5 https://dirros.openscience.si/Dokument.php?lang=slv&id=21733 Institut Jožef Stefan 0 0 0