Gmeiner B, Donnert G, Köstler H (2012)
Publication Type: Conference contribution
Publication year: 2012
Publisher: Springer
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.
City/Town: London
Pages Range: 361-374
Conference Proceedings Title: Research and Development in Intelligent Systems XXIX
Event location: Cambridge, England
ISBN: 978-1-4471-4739-8
URI: http://www.springer.com/computer/ai/book/978-1-4471-4738-1
DOI: 10.1007/978-1-4471-4739-8-28
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.
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.
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