Online evolution of offensive strategies in real-time strategy gaming

Author

Huat, Ch´ng Siong ; Teo, Jason

Author_Institution

Evolutionary Comput. Lab., Univ. Malaysia Sabah, Kota Kinabalu, Malaysia

fYear

2012

fDate

10-15 June 2012

Firstpage

1

Lastpage

8

Abstract

The main objective of this paper is to investigate online evolution of military unit combination strategies for winning an offensive rush in a real-time strategy (RTS) game. A modified version of Evolutionary Programming (EP) is used as the evolutionary optimizer while WARGUS is used as the RTS gaming environment. Evolution of the military unit combinations is conducted online, which means that optimization is taking place while a particular round of the RTS game is still in progress. Empirical tests show that the online evolution of military unit combination strategies is possible using EP and was able to mount successful offensive campaigns on a reliable basis against three respective built-in, human-crafted AI strategies provided in WARGUS.

Keywords

artificial intelligence; computer games; evolutionary computation; optimisation; RTS game; RTS gaming environment; WARGUS; built-in human-crafted AI strategy; evolutionary optimizer; evolutionary programming; military unit combination evolution; military unit combination strategy; offensive campaign; offensive rush; online offensive strategy evolution; real-time strategy gaming; Biological cells; Computers; Games; Learning systems; Optimization; Real time systems; computational intelligence in games; evolutionary programming; online evolution; real-time strategy games;

fLanguage

English

Publisher

ieee

Conference_Titel

Evolutionary Computation (CEC), 2012 IEEE Congress on

Conference_Location

Brisbane, QLD

Print_ISBN

978-1-4673-1510-4

Electronic_ISBN

978-1-4673-1508-1

Type

conf

DOI

10.1109/CEC.2012.6256120

Filename

6256120