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 : Maud de Tollenaere, Elisa Massi, Jeanne Barthélemy, Lise Aubin.

    Impliqué dans les projets :

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


  • Gilles Bailly, Mehdi Khamassi, Benoît Girard. Computational Model of the Transition from Novice to Expert Interaction Techniques. ACM Transactions on Computer-Human Interaction, Association for Computing Machinery, In press. ⟨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, Wiley, 2020, 00, pp.1 - 24. ⟨10.1111/ejn.14869⟩. ⟨hal-02899718⟩
  • Stephane Doncieux, Nicolas Bredeche, Léni 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), Springer Verlag, 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, Nature Publishing Group, 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, Nature Publishing Group, 2019, 9 (1), pp.19904. ⟨10.1038/s41598-019-56345-7⟩. ⟨hal-02426564⟩
  • François Cinotti, Alain Marchand, Matthew Roesch, Benoît Girard, Mehdi Khamassi. Impacts of inter-trial interval duration on a computational model of sign-tracking vs. goal-tracking behaviour. Psychopharmacology, Springer Verlag, 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, Elsevier, 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, American Physiological Society, 2018, ⟨10.1152/jn.00145.2018⟩. ⟨hal-02323528⟩
  • Raja Chatila, Erwan Renaudo, Mihai Andries, Omar Chavez-Garcia, Pierre Luce-Vayrac, et al.. Toward Self-Aware Robots. Frontiers in Robotics and AI, Frontiers Media S.A., 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, GitHub, 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, World Scientific, 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, Elsevier, 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, Frontiers, 2018, 12, pp.59. ⟨10.3389/fnbot.2018.00059⟩. ⟨hal-01889947⟩
  • Nicolas Rougier, Konrad Hinsen, Frédéric Alexandre, Thomas Arildsen, Lorena Barba, et al.. Sustainable computational science: the ReScience initiative. PeerJ Computer Science, PeerJ, 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, Nature Publishing Group, 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, Techniques de l'ingénieur, 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), Association pour la Recherche sur la Cognition, 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, GitHub, 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, Public Library of Science, 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, Frontiers, 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, American Physiological Society, 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, Elsevier, 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, Elsevier, 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, Frontiers, 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⟩
  • Jean Liénard, Benoît Girard. A biologically constrained model of the whole basal ganglia addressing the paradoxes of connections and selection. Journal of Computational Neuroscience, Springer Verlag, 2014, 36 (3), pp.445-468. ⟨10.1007/s10827-013-0476-2⟩. ⟨hal-01182077⟩
  • 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⟩
  • Ignasi Cos, Mehdi Khamassi, Benoît Girard. Modeling the Learning of Biomechanics and Visual Planning for Decision-Making of Motor Actions.. Journal of Physiology - Paris, Elsevier, 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, Springer Verlag, 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, IOP Publishing, 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⟩
  • Steve N'Guyen, Patrick Pirim, Jean-Arcady Meyer, Benoît Girard. An Integrated Neuromimetic Model of the Saccadic Eye Movements for the Psikharpax Robot.. International Conference on Simulation of Adaptive Behavior (SAB2010), Aug 2010, Paris, France. pp.114--125. ⟨hal-00514258⟩
  • Jean Liénard, Agnès Guillot, Benoît Girard. Multi-Objective Evolutionary Algorithms to Investigate Neurocomputational Issues : The Case Study of Basal Ganglia Models. From animals to animats 11: Simulation of Adaptive Behavior, Aug 2010, Paris, France. pp.597-606. ⟨hal-00645915⟩
  • Minh Tuan Tran, Philippe Souères, Michel Taïx, Benoît Girard. Eye-centered vs body-centered reaching control: A robotics insight into the neuroscience debate. Robotics and Biomimetics (ROBIO), 2009 IEEE International Conference on, Dec 2009, Guilin, China. pp.568-573, ⟨10.1109/ROBIO.2009.5420609⟩. ⟨hal-01525181⟩