Scalable Adaptive Serious Games using Agent Organizations(Extended Abstract)

摘要

Serious games and other training applications have the requirement that they should be suitable for trainees with different skill levels. Current approaches either use human experts or a completely centralized approach for this adaptation. These centralized approaches become very impractical and will not scale if the complexity of the game increases. Agents can be used in serious game implementations as a means to reduce complexity and increase believability but without some centralized coordination it becomes practically impossible to follow the intended storyline of the game and select suitable difficulties for the trainee. In this abstract we show that using agent organizations to coordinate the agents is scalable and allows adaptation in very complex scenarios while making sure that both the storyline and the right difficulty level for the trainee are preserved.