TY - GEN
T1 - A spatially-structured PCG method for content diversity in a physics-based simulation game
AU - Lara-Cabrera, Raúl
AU - Gutierrez-Alcoba, Alejandro
AU - Fernández-Leiva, Antonio J.
N1 - Publisher Copyright:
© Springer International Publishing Switzerland 2016.
Copyright:
Copyright 2018 Elsevier B.V., All rights reserved.
PY - 2016/3/15
Y1 - 2016/3/15
N2 - This paper presents a spatially-structured evolutionary algorithm (EA) to procedurally generate game maps of different levels of difficulty to be solved, in Gravityvolve!, a physics-based simulation videogame that we have implemented and which is inspired by the n-body problem, a classical problem in the field of physics and mathematics. The proposal consists of a steady-state EA whose population is partitioned into three groups according to the difficulty of the generated content (hard, medium or easy) which can be easily adapted to handle the automatic creation of content of diverse nature in other games. In addition, we present three fitness functions, based on multiple criteria (i.e., intersections, gravitational acceleration and simulations), that were used experimentally to conduct the search process for creating a database of maps with different difficulty in Gravityvolve!.
AB - This paper presents a spatially-structured evolutionary algorithm (EA) to procedurally generate game maps of different levels of difficulty to be solved, in Gravityvolve!, a physics-based simulation videogame that we have implemented and which is inspired by the n-body problem, a classical problem in the field of physics and mathematics. The proposal consists of a steady-state EA whose population is partitioned into three groups according to the difficulty of the generated content (hard, medium or easy) which can be easily adapted to handle the automatic creation of content of diverse nature in other games. In addition, we present three fitness functions, based on multiple criteria (i.e., intersections, gravitational acceleration and simulations), that were used experimentally to conduct the search process for creating a database of maps with different difficulty in Gravityvolve!.
KW - Coco
KW - evolutionary algorithms
KW - human evaluation
KW - physics-based game
UR - http://www.scopus.com/inward/record.url?scp=84961720115&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-31204-0_42
DO - 10.1007/978-3-319-31204-0_42
M3 - Conference contribution
AN - SCOPUS:84961720115
SN - 9783319312033
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 653
EP - 668
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 -