Intelligent controllers as hierarchical stochastic automata

This paper introduces a design methodology for intelligent controllers, based on a hierarchical linguistic model of command translation by tasks-primitive tasks-primitive actions, and on a two-stage hierarchical learning stochastic automaton that models the translation interfaces of a three-level hierarchical intelligent controller. The methodology relies on the designer's a priori knowledge on how to implement by primitive actions the different primitive tasks which define the intelligent controller. A cost function applicable to any primitive task is introduced and used to learn on-line the optimal choices from the corresponding predesigned sets of primitive actions. The same concept applies to the optimal tasks for each command, whose choice is based on conflict sets of stochastic grammar productions. Optional designs can be compared using this performance measure. A particular design evolves towards the command translation (by tasks-primitive tasks-primitive actions) that minimizes the cost function.

[1]  Satinder Singh.  Transfer of Learning by Composing Solutions of Elemental Sequential Tasks , 1992, Mach. Learn..

[2]  Rodney A. Brooks,et al.  A Robust Layered Control Syste For A Mobile Robot , 2022 .

[3]  Kaddour Najim,et al.  Learning Automata: Theory and Applications , 1994 .

[4]  Taylor L. Booth,et al.  Grammatical Inference: Introduction and Survey - Part II , 1975, IEEE Transactions on Systems, Man, and Cybernetics.

[5]  Neville Hogan,et al.  Impedance Control: An Approach to Manipulation , 1984, 1984 American Control Conference.

[6]  King-Sun Fu,et al.  Learning Control Systems-Review and Outlook , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[7]  Richard S. Sutton,et al.  Neuronlike adaptive elements that can solve difficult learning control problems , 1983, IEEE Transactions on Systems, Man, and Cybernetics.

[8]  Frederick Mosteller,et al.  Stochastic Models for Learning , 1956 .

[9]  K. Fu,et al.  On some reinforcement techniques and their relation to the stochastic approximation , 1966 .

[10]  James S. Albus,et al.  Outline for a theory of intelligence , 1991, IEEE Trans. Syst. Man Cybern..

[11]  Fei-Yue Wang,et al.  A coordination theory for intelligent machines , 1990, Autom..

[12]  Ronald C. Arkin,et al.  Intelligent Robotic Systems , 1995, IEEE Expert.

[13]  Neville Hogan,et al.  Impedance Control: An Approach to Manipulation: Part I—Theory , 1985 .

[14]  Elizabeth C. Hirschman,et al.  Judgment under Uncertainty: Heuristics and Biases , 1974, Science.

[15]  Sukhan Lee,et al.  An accurate estimation of 3-D position and orientation of a moving object for robot stereo vision: Kalman filter approach , 1990, Proceedings., IEEE International Conference on Robotics and Automation.

[16]  Kostas J. Kyriakopoulos,et al.  Minimum jerk path generation , 1988, Proceedings. 1988 IEEE International Conference on Robotics and Automation.

[17]  Kumpati S. Narendra,et al.  Learning automata - an introduction , 1989 .

[18]  Pedro U. Lima,et al.  Design of Intelligent Control Systems Based on Hierarchical Stochastic Automata , 1996, Series in Intelligent Control and Intelligent Automation.

[19]  H. Woxniakowski.  Information-Based Complexity , 1988 .

[20]  Richard W. Prager,et al.  A Modular Q-Learning Architecture for Manipulator Task Decomposition , 1994, ICML.

[21]  A. Tversky,et al.  Judgment under uncertainty: Judgment under uncertainty: Heuristics and biases , 1982 .

[22]  Taylor L. Booth,et al.  Grammatical Inference: Introduction and Survey-Part II , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[23]  George N. Saridis,et al.  Reliability analysis in intelligent machines , 1990, Proceedings., IEEE International Conference on Robotics and Automation.

[24]  Panos J. Antsaklis,et al.  An introduction to intelligent and autonomous control , 1993 .

[25]  James H. Graham,et al.  Linguistic Decision Structures for Hierarchical Systems , 1982, IEEE Transactions on Systems, Man, and Cybernetics.

[26]  J.E. McInroy,et al.  Reliability analysis in intelligent machines , 1990, IEEE Trans. Syst. Man Cybern..

[27]  Oussama Khatib,et al.  The explicit dynamic model and inertial parameters of the PUMA 560 arm , 1986, Proceedings. 1986 IEEE International Conference on Robotics and Automation.

[28]  Long Ji Lin,et al.  Scaling Up Reinforcement Learning for Robot Control , 1993, International Conference on Machine Learning.

[29]  Taylor L. Booth,et al.  Grammatical Inference: Introduction and Survey - Part I , 1975, IEEE Trans. Syst. Man Cybern..