%A Julian Togelius %A Renzo De Nardi %A Simon M. Lucas %T Towards automatic personalised content creation for racing games %X Evolutionary algorithms are commonly used to create high-performing strategies or agents for computer games. In this paper, we instead choose to evolve the racing tracks in a car racing game. An evolvable track representation is devised, and a multiobjective evolutionary algorithm maximises the entertainment value of the track relative to a particular human player. This requires a way to create accurate models of players' driving styles, as well as a tentative definition of when a racing track is fun, both of which are provided. We believe this approach opens up interesting new research questions and is potentially applicable to commercial racing games. %D 2007 %K Games, Car Racing, Evolution, Neural Networks %I IEEE %L cogprints5573