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2016 | OriginalPaper | Buchkapitel

Constrained Level Generation Through Grammar-Based Evolutionary Algorithms

verfasst von : Jose M. Font, Roberto Izquierdo, Daniel Manrique, Julian Togelius

Erschienen in: Applications of Evolutionary Computation

Verlag: Springer International Publishing

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Abstract

This paper introduces an evolutionary method for generating levels for adventure games, combining speed, guaranteed solvability of levels and authorial control. For this purpose, a new graph-based two-phase level encoding scheme is developed. This method encodes the structure of the level as well as its contents into two abstraction layers: the higher level defines an abstract representation of the game level and the distribution of its content among different inter-connected game zones. The lower level describes the content of each game zone as a set of graphs containing rooms, doors, monsters, keys and treasure chests. Using this representation, game worlds are encoded as individuals in an evolutionary algorithm and evolved according to an evaluation function meant to approximate the entertainment provided by the game level. The algorithm is implemented into a design tool that can be used by game designers to specify several constraints of the worlds to be generated. This tool could be used to facilitate the design of game levels, for example to make professional-level content production possible for non-experts.

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Metadaten
Titel
Constrained Level Generation Through Grammar-Based Evolutionary Algorithms
verfasst von
Jose M. Font
Roberto Izquierdo
Daniel Manrique
Julian Togelius
Copyright-Jahr
2016
DOI
https://doi.org/10.1007/978-3-319-31204-0_36

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