Personalized procedural map generation in games via evolutionary algorithms

Raffe, W 2014, Personalized procedural map generation in games via evolutionary algorithms, Doctor of Philosophy (PhD), Computer Science and Information Technology, RMIT University.

Document type: Thesis
Collection: Theses

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Title Personalized procedural map generation in games via evolutionary algorithms
Author(s) Raffe, W
Year 2014
Abstract In digital games, the map (sometimes referred to as the level) is the virtual environment in which a player navigates through and interacts with during gameplay. The map outlines the boundaries of play, aids in establishing rule systems, and supports narratives. The map also directly influences the challenges that a player will experience and the pace of gameplay, a property that has previously been linked to a player's enjoyment of a game. Therefore, the entertainment value of the game is maximized by altering the challenge of a map to fit a player's expected ability. In most industry leading games, creating maps is a lengthy manual process conducted by highly trained teams of designers. However, for many decades procedural content generation (PCG) techniques have been used to automate the map creation process to provide players with a larger range of experiences than would normally be possible. However, in recent years, PCG has been proposed as a means of tailoring game content to the preferences and skills of a specific player. These approaches fall into the recently established research field known as Experience-driven PCG (EDPCG), in which knowledge about the player is included in a generate-and-test PCG framework. This thesis contributes to the growing EDPCG field with a focus on personalizing maps. Here, maps are represented via two distinct concepts; geometry and content layout. The geometry of a map defines the boundaries of play and the location of static virtual objects. Meanwhile, the content layout describes the location and quantity of interactive game assets, such as enemies and pick-ups. Both of these components affect a player's experience to varying degrees in different game genres. A third concept, player preference modelling, is added when adapting a map to a player's preferences and is conducted by collecting, interpreting, and utilizing knowledge about the player. In this thesis, these three subcomponents are studied as interlocking mechanisms of the personalized procedural map generation process and solutions are proposed for each. Firstly, geometry generation is conducted for both exterior and interior environments by connecting pre-made map segments to form larger, more complete maps. Player preferences are incorporated into this process via interactive evolutionary computing. The layout of content throughout the map is then determined by using features of the geometry as input to a Compositional Pattern-Producing Network, a population of which are evolved through Neuroevolution of Augmenting Topologies. Finally, a player's preferences for content layout are captured and utilized through the use of a player model based upon a recommender system (RS) framework. The geometry generation process is firstly implemented into an evolutionary terrain tool that was created to aid novice game developers build the terrain of a map. All the solutions are then combined into the action-shooter game PCG: Angry Bots and evaluated through a large-scale public user experiment. The solutions are shown to perform well and can be generalized to other game genres. However, the experiment also gives rise to new questions and so this thesis concludes with a look at potential future work.
Degree Doctor of Philosophy (PhD)
Institution RMIT University
School, Department or Centre Computer Science and Information Technology
Keyword(s) personalized games
procedural content generation
evolutionary computing
player modelling
machine learning
recommender systems
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Created: Fri, 12 Sep 2014, 09:41:30 EST by Maria Lombardo
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