Grant: Collaborative Research and Development Grants

Procedural content generation (PCG) represents an automatic process by which content for computer games is automatically created. As such, it has the potential to significantly reduce the cost of game development. Commercial products are available for automatically generating visual content. Moreover, there have been several results over the last five years in which significant advances have been made to PCG for describing the structural layout of material encountered in a game. Examples include the automatic generation of 'maze like worlds' as encountered in the adventure genre of computer games, and specific instances of content for platform style games - such as 'Super Mario Bros' - or physics puzzle style games such as 'Cut the Rope'. In this work, we develop PCG approaches for two gaming genres: 1) an Angry Birds style game in which the goal is to provide as diverse a range of content as possible, and 2) fighting games in which content is driven by the availability of good opponents that are able to resist the player's ability to predict their moves. Our insight for defining the PCG engine for the Angry Birds physics style game is to define solution trajectories and use this to identify constraints from which content is constructed. Variation in content will come from assuming a stochastic process for content generation, whereas the use of constraints helps guide variation operators to efficiently identify the most promising content. PCG for flighting games will make use of coevolutionary processes for automatically identifying a diverse range of strategies for flighting agent strategies. Parameterization constraints will be investigated to encourage the development of distinct fighting styles. Moreover, we are also interested in extending the pairwise model of combat typically assumed for fighting games so that several simultaneous multi-opponent modes of combat are available, thus extending the genre beyond pairwise play.