Analysis and Design of Hybrid AI/Control Systems

This paper discusses the nature of interactions between highlevel intelligent agents and low-level control algorithms. Control algorithms offer the promise of simplifying a dynamic system’s apparent behavior as perceived by an intelligent agent, thus making the agent’s task much easier. However, the coupled dynamics of such a hybrid system can be difficult to predict and may lead to undesirable behavior. We demonstrate that it is possible for a rational intelligent agent acting on a well-controlled dynamical system to cause undesirable behavior when coupled, and present a method for analyzing the resulting dynamics of such coupled, hybrid systems. A technique for alleviating these behaviors using newly developed control algorithms is then suggested. These controllers, which are adaptive in nature, also suggest he possibility of "distributing" learning and intelligence between the high and low levels of authority. A new architecture for hybrid systems encapsulating these ideas is then suggested.