Home » Teams » Amac » Mehdi Khamassi
  • Mehdi Khamassi

  • Research director
  • Team: Amac
  • Office: 65-66/306
  • Email: mehdi (dot) khamassi (at) sorbonne-universite (dot) fr
  • Phone:+33 1 44 27 28 85
  • Addresse: ISIR, Campus Pierre et Marie Curie, 4 place Jussieu, BC173, 75005 Paris
  • Website: https://pages2.isir.upmc.fr/mkhamassi/
  • Bio: Mehdi Khamassi is research director employed by the Centre National de la Recherche Scientifique (CNRS), and working at the Institute of Intelligent Systems and Robotics, Sorbonne Université, Paris, France. He has a double background in Computer Science (Engineering diploma in 2003 from Ecole Nationale Supérieure d'Informatique pour l'Industrie et l'Entreprise, Evry with specialization in Artificial Intelligence and Statistical Modeling) and Computational Neuroscience (Cogmaster in 2003 from Université Pierre et Marie Curie (UPMC), Paris). Then he pursued a PhD at UPMC and Collège de France between 2003 and 2007. He serves as director of studies for the CogMaster program at Ecole Normale Supérieure, Paris, and as Associate Editor for the journals Intellectica, Frontiers in Neurorobotics, Frontiers in Decision Neuroscience, and Neurons, Behavior, Data analysis and Theory. His main topics of research include decision-making and reinforcement learning in robots and humans, and the role of social and non-social rewards in learning.

Publications

  • Mehdi Khamassi. Neurosciences cognitives. Éditions de Boeck Supérieur, 2021. ⟨hal-03411280⟩
  • Anne Collins, Mehdi Khamassi. Initiation à la modélisation computationnelle. Khamassi, M. (Ed.) Neurosciences cognitives, 2021. ⟨hal-03411274⟩
  • Alizée Lopez-Persem, Mehdi Khamassi. Décision et action. Khamassi, M. (Ed.) Neurosciences cognitives, 2021. ⟨hal-03411266⟩
  • Paris Oikonomou, Athanasios Dometios, Mehdi Khamassi, Costas Tzafestas. Task Driven Skill Learning in a Soft-Robotic Arm*. 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2021), Sep 2021, Prague, Czech Republic. ⟨hal-03275472v2⟩
  • Lea Roumazeilles, Matthias Schurz, Mathilde Lojkiewiez, Lennart Verhagen, Urs Schüffelgen, et al.. Social prediction modulates activity of macaque superior temporal cortex. Science Advances , American Association for the Advancement of Science (AAAS), 2021, 7 (38). ⟨hal-03346442⟩
  • I Rañó, Mehdi Khamassi, K Wong-Lin. Stability Analysis of Bio-inspired Source Seeking with Noisy Sensors. 2021 European Control Conference (ECC), Jul 2021, Kongens Lyngby, Denmark. ⟨hal-03277526⟩
  • Marios Panayi, Mehdi Khamassi, Simon Killcross. The rodent lateral orbitofrontal cortex as an arbitrator selecting between model-based and model-free learning systems. Behavioral Neuroscience, American Psychological Association, 2021, 135 (2), pp.226-244. ⟨10.1037/bne0000454⟩. ⟨hal-03107588v2⟩
  • Geoffrey Schoenbaum, Mehdi Khamassi, Mathias Pessiglione, Jay Gottfried, Elisabeth Murray. The magical orbitofrontal cortex.. Behavioral Neuroscience, American Psychological Association, 2021, 135 (2), pp.108 - 108. ⟨10.1037/bne0000470⟩. ⟨hal-03251587⟩
  • Mehdi Khamassi. Adaptive coordination of multiple learning strategies in brains and robots. 9th International Conference on the Theory and Practice of Natural Computing (TPNC 2020), Dec 2020, Taoyuan, Taiwan. ⟨10.1007/978-3-030-63000-3_1⟩. ⟨hal-03277525⟩
  • Evelien H.S. Schut, Irene Navarro Lobato, Alejandra Alonso, Steven Smits, Mehdi Khamassi, et al.. The Object Space Task reveals increased expression of cumulative memory in a mouse model of Kleefstra syndrome. Neurobiology of Learning and Memory, Elsevier, 2020, 173, pp.107265. ⟨10.1016/j.nlm.2020.107265⟩. ⟨hal-02941978⟩
  • 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. IEEE RO-MAN 2020, Aug 2020, Naples, Italy. ⟨hal-02899767⟩
  • Rémi Dromnelle, Benoît Girard, Erwan Renaudo, Raja Chatila, Mehdi Khamassi. 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, (Online Conference), France. ⟨hal-02883717v2⟩
  • Marco Wittmann, Elsa Fouragnan, Davide Folloni, Miriam Klein-Flügge, Bolton Chau, et al.. Global reward state affects learning and activity in raphe nucleus and anterior insula in monkeys. Nature Communications, Nature Publishing Group, 2020, 11 (1), ⟨10.1038/s41467-020-17343-w⟩. ⟨hal-03098645⟩
  • Mariacarla Staffa, Silvia Rossi, Adriana Tapus, Mehdi Khamassi. Special Issue on Behavior Adaptation, Interaction, and Artificial Perception for Assistive Robotics. International Journal of Social Robotics, Springer, 2020, 12, pp.613 - 616. ⟨10.1007/s12369-020-00655-8⟩. ⟨hal-02864719⟩
  • Paris Oikonomou, Mehdi Khamassi, Costas Tzafestas. Periodic movement learning in a soft-robotic arm. IEEE International Conference on Robotics and Automation (ICRA 2020), May 2020, Paris (virtuel), France. ⟨10.1109/ICRA40945.2020.9197035⟩. ⟨hal-03435441⟩
  • 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⟩
  • James Gillespie, Iñaki Rañó, Nazmul Siddique, Jose Santos, Mehdi Khamassi. Using Reinforcement Learning to Attenuate for Stochasticity in Robot Navigation Controllers. 2019 IEEE Symposium Series on Computational Intelligence (SSCI 2019), Dec 2019, Xiamen, China. ⟨10.1109/SSCI44817.2019.9002834⟩. ⟨hal-02324129⟩
  • 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⟩
  • Jack Hadfield, Georgia Chalvatzaki, Petros Koutras, Mehdi Khamassi, Costas Tzafestas, et al.. A Deep Learning Approach for Multi-View Engagement Estimation of Children in a Child-Robot Joint Attention Task. 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2019), Nov 2019, Macau, China. ⟨hal-02324118⟩
  • Mehdi Khamassi, Frédéric Decremps. Apprentissage de la démarche scientifique et de l'esprit critique : un enseignement de Sorbonne Université pour les étudiants d'aujourd'hui, citoyens de demain. Bertezene, S. and Vallat, D. (Eds.) Guider la raison qui nous guide : Agir et penser en complexité, 2019. ⟨hal-02324100⟩
  • Mehdi Khamassi, Raja Chatila, Alain Mille. Éthique et sciences cognitives. Intellectica - La revue de l’Association pour la Recherche sur les sciences de la Cognition (ARCo), Association pour la Recherche sur la Cognition, 2019, 2019/1 (70), pp.7-39. ⟨hal-02324092⟩
  • 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⟩
  • Lisa Genzel, Evelien Schut, Tim Schröder, Ronny Eichler, Mehdi Khamassi, et al.. The object space task shows cumulative memory expression in both mice and rats. PLoS Biology, Public Library of Science, 2019, 17 (6), pp.e3000322. ⟨10.1371/journal.pbio.3000322⟩. ⟨hal-02323650⟩
  • 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⟩
  • Mehdi Khamassi, George Velentzas, Theodore Tsitsimis, Costas Tzafestas. Robot Fast Adaptation to Changes in Human Engagement During Simulated Dynamic Social Interaction With Active Exploration in Parameterized Reinforcement Learning. IEEE Transactions on Cognitive and Developmental Systems, Institute of Electrical and Electronics Engineers, Inc, 2018, 10 (4), pp.881-893. ⟨10.1109/TCDS.2018.2843122⟩. ⟨hal-02324064⟩
  • 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⟩
  • Sophie Bavard, Maël Lebreton, Mehdi Khamassi, Giorgio Coricelli, Stefano Palminteri. Reference-point centering and range-adaptation enhance human reinforcement learning at the cost of irrational preferences. Nature Communications, Nature Publishing Group, 2018, 9, pp.4503. ⟨10.1038/s41467-018-06781-2⟩. ⟨hal-01927184⟩
  • Brian Lee, Ronny Gentry, Gregory Bissonette, Rae Herman, John Mallon, et al.. Manipulating the revision of reward value during the intertrial interval increases sign tracking and dopamine release. PLoS Biology, Public Library of Science, 2018, 16 (9), pp.e2004015. ⟨10.1371/journal.pbio.2004015⟩. ⟨hal-02324085⟩
  • Mehdi Khamassi, G Chalvatzaki, T Tsitsimis, G Velentzas, C Tzafestas. A framework for robot learning during child-robot interaction with human engagement as reward signal. 27th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN 2018), Aug 2018, Nanjing, China. ⟨hal-02324150⟩
  • George Velentzas, Theodore Tsitsimis, Iñaki Rañó, Costas Tzafestas, Mehdi Khamassi. Adaptive reinforcement learning with active state-specific exploration for engagement maximization during simulated child-robot interaction. Paladyn: Journal of Behavioral Robotics, De Gruyter, 2018, 9 (1), pp.235-253. ⟨10.1515/pjbr-2018-0016⟩. ⟨hal-02324073⟩
  • 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⟩
  • Laurent Dollé, Ricardo Chavarriaga, Agnès Guillot, Mehdi Khamassi. Interactions of spatial strategies producing generalization gradient and blocking: A computational approach. PLoS Computational Biology, Public Library of Science, 2018, 14 (4), pp.e1006092. ⟨10.1371/journal.pcbi.1006092⟩. ⟨hal-02324053⟩
  • 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⟩
  • Mehdi Khamassi, Elisabeth Pacherie. L'action. Collins, T., Andler, D. and Tallon-Baudry, C. La cognition : du neurone à la société, Gallimard, 2018. ⟨hal-02324111⟩
  • 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⟩
  • James Gillespie, Iñaki Rañó, Nazmul Siddique, Jose Santos, Mehdi Khamassi. Reinforcement Learning for Bio-Inspired Target Seeking. Annual Conference Towards Autonomous Robotic Systems, Jul 2017, Guildford, United Kingdom. pp.637-650, ⟨10.1007/978-3-319-64107-2_52⟩. ⟨hal-01980224⟩
  • 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⟩
  • 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⟩
  • Mehdi Khamassi, Stéphane Doncieux. Nouvelles approches en Robotique Cognitive. 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.7-25. ⟨hal-01375651⟩
  • Raja Chatila, Mehdi Khamassi. La conscience d'une machine. Interstices, INRIA, 2016. ⟨hal-01352801⟩
  • 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⟩
  • Pierre de Loor, Alain Mille, Mehdi Khamassi. Intelligence artificielle: l'apport des paradigmes incarnés. Intellectica - La revue de l’Association pour la Recherche sur les sciences de la Cognition (ARCo), Association pour la Recherche sur la Cognition, 2015, Sciences de la cognition: réflexions prospectives, 2 (64), pp.27-52. ⟨hal-01250421⟩
  • 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⟩
  • Mehdi Khamassi, René Quilodran, Pierre Enel, Peter Dominey, Emmanuel Procyk. Behavioral Regulation and the Modulation of Information Coding in the Lateral Prefrontal and Cingulate Cortex. Cerebral Cortex, Oxford University Press (OUP), 2015, 25 (9), pp.3197-3218. ⟨10.1093/cercor/bhu114⟩. ⟨hal-01219972⟩
  • 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⟩