This chapter entertains the idea of deriving filtering algorithms using (deep) reinforcement learning methods. After covering the basics of reinforcement learning, it is shown that both variational inference and reinforcement learning can be viewed as instances of a generic expectation maximization problem. The equivalence between variational inference and reinforcement learning allows for developing novel filtering algorithms. The reviewed application is the battery state‐of‐charge estimation.


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    Title :

    Reinforcement Learning‐Based Filter


    Contributors:

    Published in:

    Publication date :

    2022-04-12


    Size :

    9 pages




    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English






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