Real time strategy games are complex scenarioswhere multiple agents must be coordinated
in a dynamic, partially observable environment. In this work, we model thecoordination of
these agents as a task allocation problem, in which specific tasks are given to the agents
that are more suited to execute them. We employ a task allocation algorithm based on
swarm intelligence and adjust its parameters using a genetic algorithm. To evaluate this
approach, we implement this coordination mechanism in the AI of a popular video game …

… • Automatically adjust task allocation parameters … • Many algorithms for task allocation …
– Systematic approach to adjust parameters for task allocation in complex scenarios. –
Evaluation of fitness estimation in a noisy environment. …