In this study, CMAC (Cerebellar Model Articulated Controller) neural architectures are shown to be viable for the purposes of real-time learning and control. An adaptive critic temporal difference neurocontrol design has been implemented that learns in real-time how to back up a trailer truck along a fixed straight line trajectory. The truck backer-upper experiment is a standard performance measure in the neural network literature, but previously the training of the controllers was done off-line. With the CMAC neural architectures, it was possible to train the neurocontrollers on-line in real-time on a MS-DOS PC 386.


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    Title :

    Controlling a truck with an adaptive critic temporal difference CMAC design


    Contributors:


    Publication date :

    1993-01-01


    Type of media :

    Conference paper


    Type of material :

    No indication


    Language :

    English


    Keywords :


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