TY - GEN
T1 - Constrained level generation through grammar-based evolutionary algorithms
AU - Font, Jose M.
AU - Izquierdo, Roberto
AU - Manrique, Daniel
AU - Togelius, Julian
N1 - Publisher Copyright:
© Springer International Publishing Switzerland 2016.
PY - 2016
Y1 - 2016
N2 - 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.
AB - 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.
KW - Evolutionary computation
KW - Genetic programming
KW - Procedural content generation
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U2 - 10.1007/978-3-319-31204-0_36
DO - 10.1007/978-3-319-31204-0_36
M3 - Conference contribution
AN - SCOPUS:84961711416
SN - 9783319312033
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 558
EP - 573
BT - Applications of Evolutionary Computation - 19th European Conference, EvoApplications 2016, Proceedings
A2 - Burelli, Paolo
A2 - Squillero, Giovanni
PB - Springer Verlag
T2 - 19th European Conference on Applications of Evolutionary Computation, EvoApplications 2016
Y2 - 30 March 2016 through 1 April 2016
ER -