Search Results - Dromnelle, Rémi

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  1. 1
    Computational noise in reward-guided learning drives behavioral variability in volatile environments

    Computational noise in reward-guided learning drives behavioral variability in volatile environments by Findling, Charles, Skvortsova, Vasilisa, Dromnelle, Rémi, Palminteri, Stefano, Wyart, Valentin

    Published in Nature neuroscience
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  2. 2
    Reducing Computational Cost During Robot Navigation and Human–Robot Interaction with a Human-Inspired Reinforcement Learning Architecture

    Reducing Computational Cost During Robot Navigation and Human–Robot Interaction with a Human-Inspired Reinforcement Learning Architecture by Dromnelle, Rémi, Renaudo, Erwan, Chetouani, Mohamed, Maragos, Petros, Chatila, Raja, Girard, Benoît, Khamassi, Mehdi

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  3. 3
    Coping with the variability in humans reward during simulated human-robot interactions through the coordination of multiple learning strategies

    Coping with the variability in humans reward during simulated human-robot interactions through the coordination of multiple learning strategies by Dromnelle, Remi, Girard, Benoit, Renaudo, Erwan, Chatila, Raja, Khamassi, Mehdi

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  4. 4
    Model-Based and Model-Free Replay Mechanisms for Reinforcement Learning in Neurorobotics

    Model-Based and Model-Free Replay Mechanisms for Reinforcement Learning in Neurorobotics by Massi, Elisa, Barthélemy, Jeanne, Mailly, Juliane, Dromnelle, Rémi, Canitrot, Julien, Poniatowski, Esther, Girard, Benoît, Khamassi, Mehdi

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  5. 5
    Coping with the variability in humans reward during simulated human-robot interactions through the coordination of multiple learning strategies

    Coping with the variability in humans reward during simulated human-robot interactions through the coordination of multiple learning strategies by Dromnelle, Rémi, Girard, Benoît, Renaudo, Erwan, Chatila, Raja, Khamassi, Mehdi

    Published in arXiv.org
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  6. 6
    How to reduce computation time while sparing performance during robot navigation? A neuro-inspired architecture for autonomous shifting between model-based and model-free learning

    How to reduce computation time while sparing performance during robot navigation? A neuro-inspired architecture for autonomous shifting between model-based and model-free learning by Dromnelle, Rémi, Renaudo, Erwan, Pourcel, Guillaume, Chatila, Raja, Girard, Benoît, Khamassi, Mehdi

    Published in arXiv.org
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