The goal of this research is to apply reinforcement learning methods to real-world problems like scheduling. In this preliminary paper, we show that learning to solve scheduling problems such as the Space Shuttle Payload Processing and the Automatic Guided Vehicle (AGV) scheduling can be usefully studied in the reinforcement learning framework. We discuss some of the special challenges posed by the scheduling domain to these methods and propose some possible solutions we plan to implement.


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    Titel :

    Reinforcement learning in scheduling


    Beteiligte:
    Dietterich, Tom G. (Autor:in) / Ok, Dokyeong (Autor:in) / Zhang, Wei (Autor:in) / Tadepalli, Prasad (Autor:in)


    Erscheinungsdatum :

    01.01.1994


    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Keine Angabe


    Sprache :

    Englisch


    Schlagwörter :


    Reinforcement Learning in Scheduling

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