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A Multi-objective Genetic Algorithm for Build Order Optimization in StarCraft II

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Abstract

This article presents a modified version of the multi-objective genetic algorithm NSGA II in order to find optimal opening strategies in the real-time strategy game StarCraft II. Based on an event-driven simulator capable of performing an accurate estimate of in-game build-times the quality of different build lists can be judged. These build lists are used as chromosomes within the genetic algorithm. Procedural constraints e.g. given by the Tech-Tree or other game mechanisms, are implicitly encoded into them. Typical goals are to find the build list producing most units of one or more certain types up to a certain time (Rush) or to produce one unit as early as possible (Tech-Push). Here, the number of entries in a build list varies and the objective values have in contrast to the search space a very small diversity. We introduce our game simulator including its graphical user interface, the modifications necessary to fit the genetic algorithm to our problem, test our algorithm on different Tech-Pushes and Rushes for all three races, and validate it with empirical data of expert StarCraft II players.

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Notes

  1. ©2010 Blizzard Entertainment, Inc. All rights reserved. Wings of Liberty is a trademark, and StarCraft and Blizzard Entertainment are trademarks or registered trademarks of Blizzard Entertainment, Inc. in the U.S. and/or other countries.

  2. http://blizzard.com/en-us/games/sc2/.

  3. http://eu.battle.net/de/.

  4. http://us.battle.net/sc2/en/game/race/terran|zerg|protoss/techtree/wol.

  5. http://www.microsoft.com/germany/visualstudio/.

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  1. Cauerstr. 11, 91058, Erlangen, Germany

    Harald Köstler & Björn Gmeiner

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  1. Harald Köstler
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  2. Björn Gmeiner
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Correspondence to Harald Köstler.

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Köstler, H., Gmeiner, B. A Multi-objective Genetic Algorithm for Build Order Optimization in StarCraft II. Künstl Intell 27, 221–233 (2013). https://doi.org/10.1007/s13218-013-0263-2

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