An open problem in hierarchical reinforcement learning is how to automatically generate hierarchies, e.g. options. We consider an immune clustering approach for automatic construction of options in a dynamic environment. The learning agent generates an undirected edge-weighted topological graph of the environment state transitions online. An immune clustering algorithm is then used to partition the state space. A second immune response algorithm is used to update the clusters when a new state being encountered later. Local strategies for reaching the different parts of the space are separately learned and added to the model in a form of options. By our approach, the options not only can be automatically generated but also can be dynamically updated.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Automatic option generation in hierarchical reinforcement learning via immune clustering


    Beteiligte:
    Jing Shen, (Autor:in) / Guochang Gu, (Autor:in) / Haibo Liu, (Autor:in)


    Erscheinungsdatum :

    01.01.2006


    Format / Umfang :

    2823841 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Dynamic Option Policy Enabled Hierarchical Deep Reinforcement Learning Model for Autonomous Overtaking Maneuver

    Singh Lodhi, Shikhar / Kumar, Neetesh / Kumar Pandey, Pradumn | IEEE | 2025


    AUTONOMOUS BEHAVIOR GENERATION WITH HIERARCHICAL REINFORCEMENT LEARNING

    SOLEYMAN SEAN / KHOSLA DEEPAK | Europäisches Patentamt | 2021

    Freier Zugriff

    Automatic driving non-signalized intersection decision generation method based on hierarchical reinforcement learning

    CHEN XUEMEI / TANG YUNHAO / HAO JIACHEN et al. | Europäisches Patentamt | 2024

    Freier Zugriff

    Automatic driving method and device based on hierarchical reinforcement learning

    MAO ZHIQI / PENG LIHUI / YAO DANYA et al. | Europäisches Patentamt | 2023

    Freier Zugriff

    Hierarchical Reinforcement Learning Under Mixed Observability

    Nguyen, Hai / Yang, Zhihan / Baisero, Andrea et al. | TIBKAT | 2023