Optimizing Opening Strategies in a Real-time Strategy Game by a Multi-objective Genetic Algorithm

Conference contribution


Publication Details

Author(s): Gmeiner B, Donnert G, Köstler H
Title edited volumes: Res. and Dev. in Intelligent Syst. XXIX: Incorporating Applications and Innovations in Intel. Sys. XX - AI 2012, 32nd SGAI Int. Conf. on Innovative Techniques and Applications of Artificial Intel.
Publisher: Springer
Publishing place: London
Publication year: 2012
Conference Proceedings Title: Research and Development in Intelligent Systems XXIX
Pages range: 361-374
ISBN: 978-1-4471-4739-8


Abstract

This paper presents modeling, forward simulation, and optimization of different opening strategies in the real-time strategy game Starcraft 2. We implemented an event-driven simulator in C# with graphical user interface. In order to find optimal build orders, we employ a modified version of the multi-objective genetic algorithm NSGA II. Procedural constraints e.g. given by the tech-tree or other game mechanisms, are implicitly encoded into the chromosomes. Additionally, the size of the active part of the chromosomes is not known a priori, and the objectives values have a small diversity. The model was tested on different Tech-Pushes and Rushes, and validated with empirical data of expert Starcraft 2 players. © Springer-Verlag London 2012.


FAU Authors / FAU Editors

Gmeiner, Björn Dr.-Ing.
Lehrstuhl für Informatik 10 (Systemsimulation)
Köstler, Harald Prof. Dr.
Lehrstuhl für Informatik 10 (Systemsimulation)


How to cite

APA:
Gmeiner, B., Donnert, G., & Köstler, H. (2012). Optimizing Opening Strategies in a Real-time Strategy Game by a Multi-objective Genetic Algorithm. In Research and Development in Intelligent Systems XXIX (pp. 361-374). Cambridge, England: London: Springer.

MLA:
Gmeiner, Björn, Gerald Donnert, and Harald Köstler. "Optimizing Opening Strategies in a Real-time Strategy Game by a Multi-objective Genetic Algorithm." Proceedings of the SGAI International Conference on Artificial Intelligence, Cambridge, England London: Springer, 2012. 361-374.

BibTeX: 

Last updated on 2018-25-09 at 15:23