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Erschienen in:
2012 | OriginalPaper | Buchkapitel
Optimizing Opening Strategies in a Real-time Strategy Game by a Multi-objective Genetic Algorithm
verfasst von : Björn Gmeiner, Gerald Donnert, Harald Köstler
Erschienen in: Research and Development in Intelligent Systems XXIX
Verlag: Springer London
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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.