De Nardi, R;
Towards automatic personalised content creation for racing games.
2007 IEEE Symposium on Computational Intelligence and Games.
(pp. 252 - 259).
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.
|Title:||Towards automatic personalised content creation for racing games|
|Event:||IEEE Symposium on Computational Intelligence and Games|
|Dates:||2007-04-01 - 2007-04-05|
|Keywords:||car racing, player modelling, entertainment metrics, content creation, evolution|
|UCL classification:||UCL > School of BEAMS > Faculty of Engineering Science
UCL > School of BEAMS > Faculty of Engineering Science > Computer Science
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