Embodied agents can be a powerful interface for natural human-computer interaction. While graphical realism is steadily increasing, the complexity of believable behavior is still hard to create and maintain. We propose a hybrid and modular approach to modeling the agent’s control, combining state charts and rule processing. This allows us to choose the most appropriate method for each of the various behavioral processes, e.g. state charts for deliberative processes and rules for reactive behaviors. Our long-term goal is to architect a framework where the overall control is split into modules and submodules employing appropriate control methods, such as state-based or rule-based technology, so that complex yet maintainable behavior can be modeled.