A method of training a deep reinforcement learning model for autonomous control of a machine, such as autonomous vehicles, the model being configured to output, by a policy network, an agent action in response to input of state information and a value function, the agent action representing a control signal for the machine. The method comprises minimizing a loss function of the policy network; wherein the loss function of the policy network comprises an autonomous guidance component and a human guidance component (human intervention); and wherein the autonomous guidance component is zero when the state information is indicative of a human input signal.


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    Title :

    AUTONOMOUS DRIVING METHODS AND SYSTEMS


    Contributors:
    LYU CHEN (author) / WU JINGDA (author)

    Publication date :

    2024-05-16


    Type of media :

    Patent


    Type of material :

    Electronic Resource


    Language :

    English


    Classification :

    IPC:    G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen / B60W CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION , Gemeinsame Steuerung oder Regelung von Fahrzeug-Unteraggregaten verschiedenen Typs oder verschiedener Funktion



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