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    Reinforcement learning· 2018

    Recurrent World Models Facilitate Policy Evolution

    David Ha (first author) · 2018

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    DOI 10.48550/arxiv.1809.01999arXiv 1803.10122OpenAlex W2890208753

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    Why it matters

    Popularized learning compact generative environment models and training policies within imagined simulations.

    Condensed from the expert lists' notes.

    The record

    First released
    2018 (from arXiv 1803.10122)
    Citations
    2,233 citations, as counted by Papers With Code (CC BY-SA 4.0)
    Named by
    both expert lists
    Score
    0.269 · computed rank 681 · consensus 0.44, must-read 0, citations percentile 0.391 (2010s · reinforcement-learning), awards 0, existing lists 0. Method

    Data sources

    Catalogue data from OpenAlex (CC0), Crossref (CC0 metadata; no abstracts are shown), arXiv, and Papers With Code (CC BY-SA 4.0). Each count names its source. See the method.