Described is a method for improved performance of agent-based machine learning. The method includes training a reinforcement learning (RL) agent on an image processing task. A dataset of states and corresponding actions is then extracted from the RL agent. A measure of attention is applied to an input space of the RL agent. During action selection by the RL agent, image patches of the input space are extracted based on the applied measure of attention. Portions of a set of inputs are clustered based on similarity to the image patches, generating a set of clusters having cluster centers. Non-semantic concept labels are provided as distances to the cluster centers for each state in the dataset.


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    Title :

    System and method for unsupervised concept extraction from reinforcement learning agents


    Contributors:

    Publication date :

    2025-02-11


    Type of media :

    Patent


    Type of material :

    Electronic Resource


    Language :

    English


    Classification :

    IPC:    G06V / 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 / G06F ELECTRIC DIGITAL DATA PROCESSING , Elektrische digitale Datenverarbeitung