Please use this identifier to cite or link to this item: https://www.um.edu.mt/library/oar/handle/123456789/29465
Title: Evolving missions to create game spaces
Authors: Karavolos, Daniel
Liapis, Antonios
Yannakakis, Georgios N.
Keywords: Artificial intelligence
Topology
Mutation testing of computer programs
Graph theory -- Data processing
Issue Date: 2016
Publisher: IEEE Computer Society
Citation: Karavolos, D., Liapis, A., & Yannakakis, G. N. (2016). Evolving missions to create game spaces. 2016 IEEE Conference on Computational Intelligence and Games, Santorini. 1-8.
Abstract: This paper describes a search-based generative method which creates game levels by evolving the intended sequence of player actions rather than their spatial layout. The proposed approach evolves graphs where nodes representing player actions are linked to form one or more ways in which a mission can be completed. Initially simple graphs containing the mission’s starting and ending nodes are evolved via mutation operators which expand and prune the graph topology. Evolution is guided by several objective functions which capture game design patterns such as exploration or balance; experiments in this paper explore how these objective functions and their combinations affect the quality and diversity of the evolved mission graphs.
URI: https://www.um.edu.mt/library/oar//handle/123456789/29465
Appears in Collections:Scholarly Works - InsDG

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