Potential-Field-Based Unit Behavior Optimization for Balancing in StarCraft II

Beitrag bei einer Tagung
(Konferenzbeitrag)


Details zur Publikation

Autor(en): Schmitt J, Seufert S, Zoubek C, Köstler H
Herausgeber: ACM
Jahr der Veröffentlichung: 2015
Tagungsband: GECCO Companion '15 Proceedings of the Companion Publication of the 2015 Annual Conference on Genetic and Evolutionary Computation
Seitenbereich: 1481-1482
ISBN: 978-1-4503-3488-4


Abstract

This article presents an evolutionary algorithm for optimizing the
offensive behavior of opposing units in the real-time strategy game
StarCraft II. Encounters between different unit groups are examined and
described. The goal for each group is to deal maximal damage to the
opposing group while receiving a minimal amount of damage at the same
time. The actions each unit performs are determined by accumulating a
number of predefined potential fields. Dependent on the statistics of
the involved units, the parameters of these fields then fully describe
the behavior of each individual unit. Since this includes a huge number
of possibilities, the set of optimal parameter values for both groups in
an encounter is obtained by applying an evolutionary algorithm.


FAU-Autoren / FAU-Herausgeber

Köstler, Harald Prof. Dr.
Lehrstuhl für Informatik 10 (Systemsimulation)
Schmitt, Jonas
Lehrstuhl für Informatik 10 (Systemsimulation)
Zoubek, Christian
Lehrstuhl für Informatik 3 (Rechnerarchitektur)


Zitierweisen

APA:
Schmitt, J., Seufert, S., Zoubek, C., & Köstler, H. (2015). Potential-Field-Based Unit Behavior Optimization for Balancing in StarCraft II. In ACM (Eds.), GECCO Companion '15 Proceedings of the Companion Publication of the 2015 Annual Conference on Genetic and Evolutionary Computation (pp. 1481-1482). Madrid.

MLA:
Schmitt, Jonas, et al. "Potential-Field-Based Unit Behavior Optimization for Balancing in StarCraft II." Proceedings of the Genetic and Evolutionary Computation Conference (GECCO), Madrid Ed. ACM, 2015. 1481-1482.

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Zuletzt aktualisiert 2019-20-03 um 14:08

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