The definition and rendering of terrain maps
SIGGRAPH '86 Proceedings of the 13th annual conference on Computer graphics and interactive techniques
Modeling player experience in super mario bros
CIG'09 Proceedings of the 5th international conference on Computational Intelligence and Games
Evolving content in the galactic arms race video game
CIG'09 Proceedings of the 5th international conference on Computational Intelligence and Games
Evolution of artificial terrains for video games based on accessibility
EvoApplicatons'10 Proceedings of the 2010 international conference on Applications of Evolutionary Computation - Volume Part I
Towards a generic framework for automated video game level creation
EvoApplicatons'10 Proceedings of the 2010 international conference on Applications of Evolutionary Computation - Volume Part I
Search-based procedural content generation
EvoApplicatons'10 Proceedings of the 2010 international conference on Applications of Evolutionary Computation - Volume Part I
A fast and elitist multiobjective genetic algorithm: NSGA-II
IEEE Transactions on Evolutionary Computation
Evolving patch-based terrains for use in video games
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Digging deeper into platform game level design: session size and sequential features
EvoApplications'12 Proceedings of the 2012t European conference on Applications of Evolutionary Computation
Personalised gaming: a motivation and overview of literature
Proceedings of The 8th Australasian Conference on Interactive Entertainment: Playing the System
EvoApplications'13 Proceedings of the 16th European conference on Applications of Evolutionary Computation
Controllable procedural map generation via multiobjective evolution
Genetic Programming and Evolvable Machines
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A search-based procedural content generation (SBPCG) algorithm for strategy game maps is proposed. Two representations for strategy game maps are devised, along with a number of objectives relating to predicted player experience. A multiobjective evolutionary algorithm is used for searching the space of maps for candidates that satisfy pairs of these objectives. As the objectives are inherently partially conflicting, the algorithm generates Pareto fronts showing how these objectives can be balanced. Such fronts are argued to be a valuable tool for designers looking to balance various design needs. Choosing appropriate points (manually or automatically) on the Pareto fronts, maps can be found that exhibit good map design according to specified criteria, and could either be used directly in e.g. an RTS game or form the basis for further human design.