Title :
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
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;
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
DOI :
10.1109/CEC.2012.6256120
