A master thesis from Aalborg University
Evolving Strategies For a Real-Time Strategy Game Using Genetic Algorithms
[Udvikling af Strategier til Real-Tids Strategi Spil Ved Brug af Genetiske Algoritmer]
Author(s)
Term
4. term
Education
Publication year
2013
Submitted on
2013-06-07
Pages
88 pages
Abstract
The demand for challenging AI in commercial Real-Time Strategy games is increasing by each generation. This project explores how genetic algorithms might be used to evolve more challenging AIs, by utilizing the power of natural selection. The popular strategy game Starcraft is used a testing platform throughout the project, due to its maturity as a research platform. Two approaches to evolving a Starcraft AI is examined. One is to use a traditional genetic algorithm, and the other is to use a Estimation of Distribution Genetic Algorithm. However, only the traditional genetic algorithm is implemented and tested. The results show that it is in fact possible to evolve an AI that can successfully beat an opponent playing the same static strategy. More research is needed in order to determine if genetic algorithms can be used to evolve complete commercial grade AIs.
Keywords
Documents
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