Automatic programming of a time-optimal robot controller and an analog electrical circuit to implement the robot controller by means of genetic programming   [AP] [RC] [RC] [GP]

by

Koza, J., R., Bennett III, F., H., Keane, M., A. and Andre, D.

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Info: Proceedings of 1997 IEEE International Symposium on Computational Intelligence in Robotics and Automation (Conference proceedings), 1997, p. 340-346
Keywords:Genetic Programming, Genetic Algorithms
Abstract:
Genetic programming [GP] is an automatic programming technique [AP] that evolves computer programs to solve, or approximately solve, problems. This paper presents two examples in which genetic programming [GP] creates a computer program for controlling a robot so that the robot moves to a specified destination point in minimal time. In the first approach, genetic programming [GP] evolves a computer program composed of ordinary arithmetic operations and conditional operations to implement a time-optimal control strategy. In the second approach, genetic programming [GP] evolves the design of an analog electrical circuit consisting of transistors, diodes, resistors, and power supplies to implement a near-optimal control strategy.
Notes:
IEEE CIRA-97
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BibTex:
@InProceedings{koza:1997:aptorcaect,
  author =       "John R. Koza and Forest H. {Bennett III} and Martin A.
                 Keane and David Andre",
  title =        "Automatic programming of a time-optimal robot
                 controller and an analog electrical circuit to
                 implement the robot controller by means of genetic
                 programming",
  booktitle =    "Proceedings of 1997 IEEE International Symposium on
                 Computational Intelligence in Robotics and Automation",
  year =         "1997",
  keywords =     "Genetic Programming, Genetic Algorithms",
  pages =        "340--346",
  address =      "Los Alamitos, CA, USA",
  publisher =    "Computer Society Press",
  URL =          "http://www-cs-faculty.stanford.edu/~koza/CIRAfly.ps",
  abstract =     "Genetic programming is an automatic programming
                 technique that evolves computer programs to solve, or
                 approximately solve, problems. This paper presents two
                 examples in which genetic programming creates a
                 computer program for controlling a robot so that the
                 robot moves to a specified destination point in minimal
                 time. In the first approach, genetic programming
                 evolves a computer program composed of ordinary
                 arithmetic operations and conditional operations to
                 implement a time-optimal control strategy. In the
                 second approach, genetic programming evolves the design
                 of an analog electrical circuit consisting of
                 transistors, diodes, resistors, and power supplies to
                 implement a near-optimal control strategy.",
  notes =        "IEEE CIRA-97",
}