Control performance as an entropy: An integrated theory for intelligent machines

Using the equivalence of the average Lagrangian to an Entropy established in Theoretical Thermodynamics, this paper expresses the average value of the performance criterion of a feedback control problem as an entropy. Thus, the optimal control problem may be recast as an information theoretic, one which minimizes the entropy of selecting the feedback controls. This unifies the treatment of all the levels of a Hierarchically Intelligent Control System by minimizing the sum of their entropies. Such a system is composed of three levels hierarchically ordered in decreasing intelligence with increasing precision: the organization level, performing information processing tasks like planning, decision making, learning and storage and retrieval of information from a long-term memory; the coordination level, dealing again with information processing tasks like learning, lower level decision making and dealing with short term memory only and the control level, which performs the execution of various tasks through hardware using feedback control methods. A mathematical programing algorithm which utilizes one step ahead entropies may be used to approximate the optimal solution of the intelligent machine problem.