Home » Teams » Amac » Benoît Girard
  • Benoît Girard

  • Directeur de Recherche
  • Équipe: Amac
  • Bureau: 306
  • Telephone:0144276381
  • Addresse: ISIR, 4 place jussieu, CC 173, 75005 Paris
  • Bio:

    Recruté Chargé de Recherche au CNRS (2005), Directeur de Recherche depuis 2015. Dirige l'équipe AMAC depuis 2019.
    Professeur Invité à l'OIST, Neural Computation Unit du Professeur K. Doya (dec. 2016-mars 2017). Médaille de bronze du CNRS (2010).
    Membre du Laboratoire de Physiologie de la Perception et de l'Action du Prof. A. Berthoz (Collège de France, CNRS) de 2003 à 2009.

    Supervise actuellement : Elisa Massi, Jeanne Barthélemy, Lise Aubin, Augustin Chartouny.

    Impliqué dans les projets :


    A participé à : DREAM (2015-2018), ANR STGT (2016-2019).

    Pour des nouvelles fraîches : Mastodon

Publications

  • Rémi Dromnelle, Erwan Renaudo, Mohamed Chetouani, Petros Maragos, Raja Chatila, et al.. Reducing computational cost during robot navigation and human-robot interaction with a human-inspired reinforcement learning architecture. International Journal of Social Robotics, 2022, ⟨10.1007/s12369-022-00942-6⟩. ⟨hal-03829879⟩
  • Jean Liénard, Lise Aubin, Ignasi Cos, Benoît Girard. Beta-Band Oscillations without Pathways: the opposing Roles of D2 and D5 Receptors in the basal ganglia. 2022. ⟨hal-03829812⟩
  • Elisa Massi, Jeanne Barthélemy, Juliane Mailly, Rémi Dromnelle, Julien Canitrot, et al.. Model-Based and Model-Free Replay Mechanisms for Reinforcement Learning in Neurorobotics. Frontiers in Neurorobotics, 2022, 16, pp.864380. ⟨10.3389/fnbot.2022.864380⟩. ⟨hal-03703727⟩
  • Gilles Bailly, Mehdi Khamassi, Benoît Girard. Computational Model of the Transition from Novice to Expert Interaction Techniques. ACM Transactions on Computer-Human Interaction, 2022, ⟨10.1145/3505557⟩. ⟨hal-03537963⟩
  • Rémi Dromnelle, Benoît Girard, Erwan Renaudo, Raja Chatila, Mehdi Khamassi. Coping with the variability in humans reward during simulated human-robot interactions through the coordination of multiple learning strategies. 29th IEEE International Conference on Robot and Human Interactive Communication (RO-MAN 2020), Aug 2020, Naples (en ligne), Italy. ⟨10.1109/RO-MAN47096.2020.9223451⟩. ⟨hal-02899767v2⟩
  • Rémi Dromnelle, Erwan Renaudo, Guillaume Pourcel, Raja Chatila, Benoît Girard, et al.. 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. Living Machines, Jul 2020, Freiburg (on line conference), Germany. ⟨10.1007/978-3-030-64313-3_8⟩. ⟨hal-02883717v3⟩
  • Benoît Girard, Jean Liénard, Carlos Enrique Gutierrez, Bruno Delord, Kenji Doya. Computational Neuroscience A biologically constrained spiking neural network model of the primate basal ganglia with overlapping pathways exhibits action selection. European Journal of Neuroscience, 2020, 00, pp.1 - 24. ⟨10.1111/ejn.14869⟩. ⟨hal-02899718⟩
  • Stephane Doncieux, Nicolas Bredeche, Léni Kenneth Le Goff, Benoît Girard, Alexandre Coninx, et al.. DREAM Architecture: a Developmental Approach to Open-Ended Learning in Robotics. 2020. ⟨hal-02562103⟩
  • Frédéric Alexandre, Peter Ford Dominey, Philippe Gaussier, Benoît Girard, Mehdi Khamassi, et al.. When Artificial Intelligence and Computational Neuroscience meet. Springer. A guided tour of artificial intelligence research, Interfaces and applications of artificial intelligence, 3, 2020, Interfaces and Applications of Artificial Intelligence, 978-3-030-06170-8. ⟨hal-01735123⟩
  • Mehdi Khamassi, Benoît Girard. Modeling awake hippocampal reactivations with model-based bidirectional search. Biological Cybernetics (Modeling), 2020, 114 (2), pp.231-248. ⟨10.1007/s00422-020-00817-x⟩. ⟨hal-02504897⟩
  • Benoît Girard. The seven donkeys: Super A.I. performance in animal categorization by an immature Human brain. 2019. ⟨hal-02421660⟩
  • François Cinotti, Virginie Fresno, Nassim Aklil, Etienne Coutureau, Benoît Girard, et al.. Dopamine blockade impairs the exploration-exploitation trade-off in rats. Scientific Reports, 2019, 9 (1), ⟨10.1038/s41598-019-43245-z⟩. ⟨hal-02121649⟩
  • Bénédicte Babayan, Aurélie Watilliaux, Guillaume Viejo, Anne-Lise Paradis, Benoît Girard, et al.. Author Correction: A hippocampo-cerebellar centred network for the learning and execution of sequence-based navigation. Scientific Reports, 2019, 9 (1), pp.19904. ⟨10.1038/s41598-019-56345-7⟩. ⟨hal-02426564⟩
  • François Cinotti, Alain Marchand, Matthew R Roesch, Benoît Girard, Mehdi Khamassi. Impacts of inter-trial interval duration on a computational model of sign-tracking vs. goal-tracking behaviour. Psychopharmacology, 2019. ⟨hal-02270920⟩
  • Benoît Girard. Basal Ganglia: Control of Saccades. Encyclopedia of Computational Neuroscience, Springer New York, pp.1-3, 2019, ⟨10.1007/978-1-4614-7320-6_516-2⟩. ⟨hal-02347368⟩
  • Guillaume Viejo, Benoît Girard, Emmanuel Procyk, Mehdi Khamassi. Adaptive coordination of working-memory and reinforcement learning in non-human primates performing a trial-and-error problem solving task. Behavioural Brain Research, 2018, 355, pp.76-89. ⟨10.1016/j.bbr.2017.09.030⟩. ⟨hal-01624253⟩
  • Romain Cazé, Mehdi Khamassi, Lise Aubin, Benoît Girard. Hippocampal replays under the scrutiny of reinforcement learning models. Journal of Neurophysiology, 2018, ⟨10.1152/jn.00145.2018⟩. ⟨hal-02323528⟩
  • Raja Chatila, Erwan Renaudo, Mihai Andries, Omar Ricardo Chavez-Garcia, Pierre Luce-Vayrac, et al.. Toward Self-Aware Robots. Frontiers in Robotics and AI, 2018, 5, pp.88. ⟨10.3389/frobt.2018.00088⟩. ⟨hal-01856931⟩
  • Lise Aubin, Mehdi Khamassi, Benoît Girard. Prioritized Sweeping Neural DynaQ with Multiple Predecessors, and Hippocampal Replays. Biomimetic and Biohybrid Systems. Living Machines 2018., Jul 2018, Paris, France. pp.16-27, ⟨10.1007/978-3-319-95972-6_4⟩. ⟨hal-01709275⟩
  • Romain Cazé, Marcel Stimberg, Benoît Girard. [Re] Non-Additive Coupling Enables Propagation of Synchronous Spiking Activity in Purely Random Networks. The ReScience journal, 2018, 4 (1), ⟨10.5281/zenodo.1246659⟩. ⟨hal-01856930⟩
  • Nassim Aklil, Benoît Girard, Ludovic Denoyer, Mehdi Khamassi. Sequential Action Selection and Active Sensing for Budgeted Localization in Robot Navigation. International Journal of Semantic Computing, 2018, 12 (01), pp.109-127. ⟨10.1142/S1793351X18400068⟩. ⟨hal-02324047⟩
  • Isabelle Leang, Stéphane Herbin, Benoît Girard, Jacques Droulez. On-line fusion of trackers for single-object tracking. Pattern Recognition, 2018, 74, pp.459-473. ⟨10.1016/j.patcog.2017.09.026⟩. ⟨hal-01635420⟩
  • Stéphane Doncieux, David Filliat, Natalia Díaz-Rodríguez, Timothy Hospedales, Richard Duro, et al.. Open-Ended Learning: A Conceptual Framework Based on Representational Redescription. Frontiers in Neurorobotics, 2018, 12, pp.59. ⟨10.3389/fnbot.2018.00059⟩. ⟨hal-01889947⟩
  • Nicolas P. Rougier, Konrad Hinsen, Frédéric Alexandre, Thomas Arildsen, Lorena Barba, et al.. Sustainable computational science: the ReScience initiative. PeerJ Computer Science, 2017, 3, pp.e142. ⟨10.7717/peerj-cs.142⟩. ⟨hal-01592078⟩
  • Nassim Aklil, Benoît Girard, Mehdi Khamassi, Ludovic Denoyer. Sequential Action Selection for Budgeted Localization in Robots. IEEE Robotic Computing 2017, IEEE, Apr 2017, Taichung, Taiwan. pp.97 - 100, ⟨10.1109/IRC.2017.19⟩. ⟨hal-01524808⟩
  • Bénédicte Babayan, Aurélie Watilliaux, Guillaume Viejo, Anne-Lise Paradis, Benoît Girard, et al.. A hippocampo-cerebellar centred network for the learning and execution of sequence-based navigation. Scientific Reports, 2017, 7, pp.17812. ⟨10.1038/s41598-017-18004-7⟩. ⟨hal-01668433⟩
  • Benoît Girard, Mehdi Khamassi. Coopération de systèmes d’apprentissage par renforcement multiples.. Techniques de l'Ingenieur, 2016, pp.S7793. ⟨hal-01524743⟩
  • Mehdi Khamassi, Benoît Girard, Aurélie Clodic, Sandra Devin, Erwan Renaudo, et al.. Integration of Action, Joint Action and Learning in Robot Cognitive Architectures. Intellectica - La revue de l’Association pour la Recherche sur les sciences de la Cognition (ARCo), 2016, 2016/1 (65), pp.169-203. ⟨10.3406/intel.2016.1794⟩. ⟨hal-01375666⟩
  • Guillaume Viejo, Benoît Girard, Mehdi Khamassi. [Re] Speed/accuracy trade-off between the habitual and the goal-directed processes. The ReScience journal, 2016, 2 (1), ⟨10.5281/zenodo.45852⟩. ⟨hal-01524285⟩
  • Encarni Marcos, Ignasi Cos, Benoît Girard, Paul F. M. J. Verschure. Motor Cost Influences Perceptual Decisions. PLoS ONE, 2015, 10 (12), pp.e0144841. ⟨10.1371/journal.pone.0144841⟩. ⟨hal-01257848⟩
  • Erwan Renaudo, Sandra Devin, Benoît Girard, Raja Chatila, Rachid Alami, et al.. Learning to interact with humans using goal-directed and habitual behaviors. Ro-Man 2015, Workshop on Learning for Human-Robot Collaboration, Aug 2015, Kobe, Japan. ⟨hal-01944380⟩
  • Erwan Renaudo, Benoît Girard, Raja Chatila, Mehdi Khamassi. Which criteria for autonomously shifting between goal-directed and habitual behaviors in robots?. 2015 Joint IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob), Aug 2015, Providence, RI, United States. ⟨10.1109/devlrn.2015.7346152⟩. ⟨hal-02108755⟩
  • Guillaume Viejo, Mehdi Khamassi, Andrea Brovelli, Benoît Girard. Modeling choice and reaction time during arbitrary visuomotor learning through the coordination of adaptive working memory and reinforcement learning. Frontiers in Behavioral Neuroscience, 2015, 9, pp.225. ⟨10.3389/fnbeh.2015.00225⟩. ⟨hal-01215419⟩
  • Ignasi Cos, Benoît Girard, Emmanuel Guigon. Balancing out dwelling and moving: optimal sensorimotor synchronization. Journal of Neurophysiology, 2015, 114 (1), pp.146-158. ⟨10.1152/jn.00175.2015⟩. ⟨hal-01524646⟩
  • I Leang, S Herbin, Benoît Girard, Jacques Droulez. Prédiction sélective des traitements pour le suivi d'objet. ORASIS 2015, Jun 2015, Amiens, France. ⟨hal-01525208⟩
  • Erwan Renaudo, Benoît Girard, Raja Chatila, Mehdi Khamassi. Respective Advantages and Disadvantages of Model-based and Model-free Reinforcement Learning in a Robotics Neuro-inspired Cognitive Architecture. Procedia Computer Science, 2015, 71, pp.178-184. ⟨10.1016/j.procs.2015.12.194⟩. ⟨hal-01250157⟩
  • Charles Thurat, Steve N'Guyen, Benoît Girard. Biomimetic race model of the loop between the superior colliculus and the basal ganglia: Subcortical selection of saccade targets. Neural Networks, 2015, 67, pp.54-73. ⟨10.1016/j.neunet.2015.02.004⟩. ⟨hal-01182221⟩
  • Isabelle Leang, Stéphane Herbin, Benoît Girard, Jacques Droulez. Robust Fusion of Trackers using on-line Drift Prediction.. Advanced Concepts for Intelligent Vision Systems (ACIVS 2015), Oct 2015, Catania, Italy. pp.229-240, ⟨10.1007/978-3-319-25903-1_20⟩. ⟨hal-01524811⟩
  • Steve N'Guyen, Charles Thurat, Benoît Girard. Saccade learning with concurrent cortical and subcortical basal ganglia loops.. Frontiers in Computational Neuroscience, 2014, 8, pp.48. ⟨10.3389/fncom.2014.00048⟩. ⟨hal-01000253⟩
  • Benoît Girard. Basal Ganglia: Control of Saccades. Dieter Jaeger; Ranu Jung. Encyclopedia of Computational Neuroscience, Springer, 2014, 978-1-4614-7320-6. ⟨10.1007/978-1-4614-7320-6_516-1⟩. ⟨hal-01524798⟩
  • Erwan Renaudo, Benoît Girard, Raja Chatila, Mehdi Khamassi. Design of a Control Architecture for Habit Learning in Robots. Third International Conference, Living Machines 2014, Milan, Italy, Jul 2014, Milan, Italy. ⟨10.1007/978-3-319-09435-9_22⟩. ⟨hal-01312443⟩
  • Jean Liénard, Benoît Girard. A biologically constrained model of the whole basal ganglia addressing the paradoxes of connections and selection. Journal of Computational Neuroscience, 2014, 36 (3), pp.445-468. ⟨10.1007/s10827-013-0476-2⟩. ⟨hal-01182077⟩
  • Ignasi Cos, Mehdi Khamassi, Benoît Girard. Modeling the Learning of Biomechanics and Visual Planning for Decision-Making of Motor Actions.. Journal of Physiology - Paris, 2013, 107 (5), pp.399-408. ⟨10.1016/j.jphysparis.2013.07.004⟩. ⟨hal-01000837⟩
  • Mariella Dimiccoli, Benoît Girard, Alain Berthoz, Daniel Bennequin. Striola magica. A functional explanation of otolith geometry. Journal of Computational Neuroscience, 2013, 35 (2), pp.125-154. ⟨10.1007/s10827-013-0444-x⟩. ⟨hal-01000762⟩
  • Ignasi Cos, Pavel Rueda-Orozco, David Robbe, Benoît Girard. Learning a sequence of motor responses to attain reward: a speed-accuracy trade-off. the Twenty Second Annual Computational Neuroscience Meeting: CNS*2013, Jul 2013, paris, France. pp.P143. ⟨inserm-00842300⟩
  • Ken Caluwaerts, Mariacarla Staffa, Steve N'Guyen, Christophe Grand, Laurent Dollé, et al.. A biologically inspired meta-control navigation system for the Psikharpax rat robot.. Bioinspiration and Biomimetics, 2012, 7 (2), pp.025009. ⟨10.1088/1748-3182/7/2/025009⟩. ⟨hal-01000945⟩
  • Ken Caluwaerts, Antoine Favre-Félix, Mariacarla Staffa, Christophe Grand, Steve N'Guyen, et al.. Neuro-inspired Navigation Strategies Shifting for Robots: Integration of a Multiple Landmark Taxon Strategy. Living Machines 2012, Jul 2012, Barcelone, Spain. pp.62-73, ⟨10.1007/978-3-642-31525-1_6⟩. ⟨hal-01525152⟩
  • Francis Colas, Pierre Bessière, Benoît Girard. Maximum entropy perception-action space: a Bayesian model of eye movement selection. 30th Conf. on Bayesian Methods and Maximum Entropy in Science and Engineering (MaxEnt2010), Jul 2010, Chamonix, France. ⟨10.1063/1.3573660⟩. ⟨hal-01142599⟩
  • Cécile Masson, Benoît Girard. Decoding the Grid Cells for Metric Navigation Using the Residue Numeral System. Second International Conference on Cognitive Neurodynamics, Nov 2009, Hangzhou, China. ⟨10.1007/978-90-481-9695-1_73⟩. ⟨hal-00396447⟩
  • Benoît Girard. Modélisation neuromimétique : Sélection de l'action, navigation et exécution motrice. Neurosciences [q-bio.NC]. Université Pierre et Marie Curie - Paris VI, 2010. ⟨tel-00551248⟩