Methods, systems, and computer-readable media for using inverse reinforcement learning to learn constraints from expert demonstrations are disclosed. The constraints may be learned as a constraint function in two alternating procedures, namely policy optimization and constraint function optimization. Neural network constraint functions may be learned which can represent arbitrary constraints. Embodiments are disclosed that work in all types of environments, with either discrete or continuous state and action spaces. Embodiments are disclosed that may scale to a large set of demonstrations. Embodiments are disclosed that work with any forward CRL technique when finding the optimal policy.


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    Titel :

    SYSTEMS AND METHODS TO LEARN CONSTRAINTS FROM EXPERT DEMONSTRATIONS


    Beteiligte:
    GAURAV ASHISH (Autor:in) / POUPART PASCAL (Autor:in) / REZAEE KASRA (Autor:in) / LIU GUILIANG (Autor:in)

    Erscheinungsdatum :

    23.11.2023


    Medientyp :

    Patent


    Format :

    Elektronische Ressource


    Sprache :

    Englisch


    Klassifikation :

    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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