A SYSTEM AND CONTROL THEORETIC PERSPECTIVE ON ARTIFICIAL INTELLIGENCE PLANNING SYSTEMS

Abstract

In an artificial intelligence (At) planning system the planner generates a sequence of actions to solve a problem. Similarly, the controller in a control system produces inputs to a dynamical system to solve a problem, namely the problem of changing a system's behavior into a desirable one. A mathematical theory of Al planning systems that operate in uncertain, dynamic, and time-critical environments is not nearly as well developed as the mathematical theory of systems and control. In this paper relationships and a detailed analogy between Al planning and control system architectures and concepts are developed and discussed. These results are fundamental to the development of a mathematical theory for the modeling, analysis, and design of Al planning systems for real-time environments.