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    Reinforcement learning· 2015

    Deep Reinforcement Learning with Double Q-learning

    van Hasselt (first author) · 2015 · published 2016

    Read the original

    DOI 10.1609/aaai.v30i1.10295arXiv 1509.06461OpenAlex W2746553466

    On the reading lists

    Why it matters

    Double DQN reduces overestimation.

    Condensed from the expert lists' notes.

    The record

    First released
    2015 (from arXiv 1509.06461)
    Published
    2016
    Citations
    9,633 citations, as counted by Papers With Code (CC BY-SA 4.0)
    Named by
    both expert lists
    Score
    0.426 · computed rank 326 · consensus 0.315, must-read 0, citations percentile 0.804 (2010s · reinforcement-learning), awards 0, existing lists 0.5. 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.