Almost all computer games that are currently created use fixed scenarios or simple fixed rules to define the course of the game, which mostly results in very predictable and inflexible behavior of all the elements in the game. Current research done on dynamic adjustability in games already makes it possible for different elements to adjust to the player. However, these approaches are still using centralized control. The serious games we are investigating are constructed using complex and independent subtasks that influence each other. Using centralized control becomes impractical if the complexity and the number of adaptable elements increase. We suggest a multi-agent approach for adapting serious games to the skill level of the trainee. Using separate agents makes it easier to guarantee the natural progression of each element of the game and thus its believability. The user task is selected based on a combination of the possible situations that can be provided by the agents at that stage of the game. The task selection is thus dependent on the user model, the agent preferences and the storyline of the game. The storyline and other requirements are specified by using an agent organization framework. An update function for the user model according to the performance of the trainee, the difficulty of the task and the amount of influence of each subtask is also given.
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