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Filtering by: Creator Castellano, Michael A. Remove constraint Creator: Castellano, Michael A. Committee Member Tadepalli, Prasad Remove constraint Committee Member: Tadepalli, Prasad Contributor Fern, Alan P. Remove constraint Contributor: Fern, Alan P.

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  • Re-understanding Finite-State Representations of Recurrent Policy Networks

    Creator:
    Danesh, Mohamad H.
    Abstract:
    We propose an approach for understanding control policies represented as recurrent neural networks. Recent work has approached this problem by transforming such recurrent policy networks into finite-state machines (FSM) and then analyzing the equivalent minimized FSM. While this led to interesting insights, the minimization process can obscure a deeper understanding...
    Resource Type:
    Masters Thesis
    Full Text:
    , the minimization process can obscure a deeper understanding of a machine’s operation by merging