A Multi-objective Genetic Algorithm for Build Order Optimization in StarCraft II
dc.contributor.author | Köstler, Harald | |
dc.contributor.author | Gmeiner, Björn | |
dc.date.accessioned | 2018-01-08T09:16:41Z | |
dc.date.available | 2018-01-08T09:16:41Z | |
dc.date.issued | 2013 | |
dc.description.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. | |
dc.identifier.pissn | 1610-1987 | |
dc.identifier.uri | https://dl.gi.de/handle/20.500.12116/11357 | |
dc.publisher | Springer | |
dc.relation.ispartof | KI - Künstliche Intelligenz: Vol. 27, No. 3 | |
dc.relation.ispartofseries | KI - Künstliche Intelligenz | |
dc.subject | Genetic algorithm | |
dc.subject | Multi-objective optimization | |
dc.subject | NSGA II | |
dc.subject | Starcraft II | |
dc.title | A Multi-objective Genetic Algorithm for Build Order Optimization in StarCraft II | |
dc.type | Text/Journal Article | |
gi.citation.endPage | 233 | |
gi.citation.startPage | 221 |