Treffer: Evolving missions to create game spaces

Title:
Evolving missions to create game spaces
Authors:
Karavolos, Daniel, Liapis, Antonios, Yannakakis, Georgios N., 2016 IEEE Conference on Computational Intelligence and Games
Publisher Information:
IEEE Computer Society
Publication Year:
2016
Collection:
University of Malta: OAR@UM / L-Università ta' Malta
Subject Terms:
Artificial intelligence, Topology, Mutation testing of computer programs, Graph theory -- Data processing
Document Type:
Konferenz conference object
Language:
English
Relation:
https://www.um.edu.mt/library/oar//handle/123456789/29465
DOI:
10.1109/CIG.2016.7860396
Availability:
https://www.um.edu.mt/library/oar//handle/123456789/29465
https://doi.org/10.1109/CIG.2016.7860396
Rights:
info:eu-repo/semantics/openAccess ; The copyright of this work belongs to the author(s)/publisher. The rights of this work are as defined by the appropriate Copyright Legislation or as modified by any successive legislation. Users may access this work and can make use of the information contained in accordance with the Copyright Legislation provided that the author must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the prior permission of the copyright holder
Accession Number:
edsbas.B4022C7A
Database:
BASE

Weitere Informationen

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. ; peer-reviewed