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Towards automatic personalised content creation for racing games

By Julian Togelius, Renzo De Nardi and Simon M. Lucas


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

Topics: Artificial Intelligence
Publisher: IEEE
Year: 2007
OAI identifier:

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