A computer-implemented method of learning a policy for controlling a computercontrolled system, in particular a robot, by reinforcement learning, comprising the steps of: Observing a current state (s) of an environment of the computercontrolled system. Interacting (S12) with the environment by carrying out the steps of: Determining an action (a) by the policy, which is an actor network, depending on the current state (s), Executing the action (a) by the computercontrolled system, receiving a reward (r) and the next state (s'), and storing the interaction with the environment as an experience in a replay buffer. Sampling (13) a batch of experiences from the replay buffer. Computing (S15) Q values by at least two critic networks for the experiences in said batch. Determining a standard derivation of the Q values for the experiences in said batch for each of the critic networks. Updating (S17) critic parameters depending on the Bellman equation and adding the standard derivations as regularization.


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    Titel :

    DEVICE AND METHOD TO IMPROVE REINFORCEMENT LEARNING


    Weitere Titelangaben:

    VORRICHTUNG UND VERFAHREN ZUR VERBESSERUNG DES VERSTÄRKUNGSLERNENS
    DISPOSITIF ET PROCÉDÉ POUR AMÉLIORER L'APPRENTISSAGE PAR RENFORCEMENT


    Beteiligte:
    SOFFAIR NITSAN (Autor:in) / AVNER ORLY (Autor:in) / DI CASTRO DOTAN (Autor:in)

    Erscheinungsdatum :

    09.04.2025


    Medientyp :

    Patent


    Format :

    Elektronische Ressource


    Sprache :

    Englisch


    Klassifikation :

    IPC:    G05B Steuer- oder Regelsysteme allgemein , CONTROL OR REGULATING SYSTEMS IN GENERAL / 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 / G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen



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