Genetic programming (videotape): the movie
Genetic programming (videotape): the movie
Evolving Neural Control Systems
IEEE Expert: Intelligent Systems and Their Applications
Generality and Difficulty in Genetic Programming: Evolving a Sort
Proceedings of the 5th International Conference on Genetic Algorithms
Fractal gene regulatory networks for control of nonlinear systems
PPSN'10 Proceedings of the 11th international conference on Parallel problem solving from nature: Part II
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Equations for calculating the control force of a movable inverted pendulum are generated directly with Genetic Programming (GP). The task of a movable inverted pendulum is to control the force given a cart on which a pole is hinged, not only to keep a pole standing but also to move it to an arbitrary target position. As the results of experiments, intelligent control equations are obtained that can lean the pole toward a target position by pulling the cart in the opposite direction, and then move the cart to the target while keeping the pole standing inversely. They also have the robustness to move the cart with the pole standing to the new target position when the target is changed, even if the cart is moving to the old target position. The robustness of the problem is experimentally defined and the appropriate value of the parsimony factor in GP is identified to obtain control equations with robustness and simplicity as the solutions.