Institut des Systèmes Intelligents
et de Robotique

Liste des publications (195).


[2021ACLI4894] - Schoenbaum, G. and Khamassi, M. and Pessiglione, M. and Gottfried, J. and Murray, E. (2021). The magical orbitofrontal cortex (Editorial).
Behavioral Neuroscience. to appear.
[ BIB ]

[2021ACLI4878] - Panayi, M.* and Khamassi, M.* and Killcross, S. (2021). The rodent lateral orbitofrontal cortex as an arbitrator selecting between model-based and model-free learning systems.
Behavioral Neuroscience. Vol - Pages - (* equally contributing authors).
[ PDF | DOI | BIB ]

[2021INVI4827] - Khamassi, M. (2021). Some applications of the model-based / model-free reinforcement learning framework to Neuroscience and Robotics.
16th International Conference on the Simulation of Adaptive Behavior (Pitti, A., Boucenna, S., Gaussier, P.). Cergy, France. invited conference.
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[2021INVN4828] - Khamassi, M. (2021). Modeling hippocampal awake replay with model-based bidirectional search.
Computational neuroscience symposium (Leblois, A.) at the French Neuroscience Society Colloquium (NeuroFrance 2021). Strasbourg, France. invited conference.
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[2021ACTI4896] - Oikonomou, Paris and Dometios, Athanasios and Khamassi, Mehdi and Tzafestas, Costas S. (2021). Task Driven Skill Learning in a Soft-Robotic Arm.
IEEE IROS 2021. Pages -. Prague, Czech Republic.
[ BIB ]

[2021ACTI4882] - Rano, I. and Wong-Lin, K. and Khamassi, M. (2021). Stability Analysis of Bio-inspired Source Seeking with Noisy Sensors.
2021 European Control Conference (ECC). Pages -.
[ BIB ]

[2021COM4895] - Roumazeilles, L. and Schurz, M. and Lojkiewiez, M. and Verhagen, L. and Schüffelgen, U. and Marche, K. and Mahmoodi, A. and Emberton, A. and Simpson, K. and Joly, O. and Khamassi, M. and Rushworth, M.F.S. and Mars, R.B. and Sallet, J. (2021). Social prediction modulates activity of macaque superior temporal cortex.
Poster at the NeuroFrance 2021 meeting of French Neuroscience Society. Strasbourg, France.
[ BIB ]


[2020ACLI4779] - Khamassi, M. and Girard, B. (2020). Modeling awake hippocampal reactivations with model-based bidirectional search.
Biological Cybernetics. Vol 114 Pages 231-248.
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[2020ACLI4815] - Staffa, M. and Rossi, S. and Tapus, A. and Khamassi, M. (2020). Behavior Adaptation, Interaction and Artificial Perception for Assistive Robotics (Editorial).
International Journal of Social Robotics. Vol 12 No 3 Pages 613-616.
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[2020ACLI4818] - Wittmann, M.K. and Fouragnan, E. and Folloni, D. and Klein-Flügge, M.C. and Chau, B. and Khamassi, M. and Rushworth, M.F.S. (2020). Global reward state affects learning, the raphe nucleus, and anterior insula in monkeys.
Nature Communications. Vol 11 No 1 Pages 1-17.
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[2020ACLI4823] - Schut, E.H. and Alonso, A. and Smits, S. and Khamassi, M. and Samanta, A. and Negwer, M. and Kasri, N.N. and Navarro Lobato, I. and Genzel, L. (2020). The Object Space Task reveals increased expression of cumulative memory in a mouse model of Kleefstra Syndrome.
Neurobiology of Learning and Memory. Vol 173 Pages 107265.
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[2020COS4521] - Alexandre, F. and Dominey, P.F. and Gaussier, P. and Girard, B. and Khamassi, M. and Rougier, N.P. (2020). When Artificial Intelligence and Computational Neuroscience meet.
Marquis, P., Papini, O. and Prade, H. (Eds.) A guided tour of artificial intelligence research, Vol. 3 Interfaces and applications of artificial intelligence, Heidelberg, Germany: Springer-Verlag, publisher. Pages 303-335.
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[2020INVI4826] - Khamassi, M. (2020). Hippocampal replay through the lenses of reinforcement learning.
New advances in brain-inspired perception, interaction and learning (BRAIN-PIL) workshop, IEEE ICRA 2020 Conference (Celikel, T., Díaz-Rodríguez, N., Filliat, D., Kaboli, M., Lanillos, P.). Sorbonne Université, Paris, France. invited conference.
[ BIB ]

[2020ACTI4780] - Oikonomou, P. and Khamassi, M. and Tzafestas, C. (2020). Periodic movement learning in a soft-robotic arm.
IEEE ICRA 2020. Pages -. Paris, France.
[ BIB ]

[2020ACTI4816] - Dromnelle, R. and Renaudo, E. and Pourcel, G. and Chatila, R. and Girard, B. and Khamassi, M. (2020). 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.
9th International conference on biomimetic & biohybrid systems (Living Machines 2020). Pages 1-12. Online conference (initially planned in Freiburg, Germany).
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[2020ACTI4817] - Dromnelle, R. and Girard, B. and Renaudo, E. and Chatila, R. and Khamassi, M. (2020). Coping with the variability in humans reward during simulated human-robot interactions through the coordination of multiple learning strategies.
Proceedings ofthe 29th IEEE International Conference on Robot and Human Interactive Communication (RO-MAN 2020), IEEE, publisher. Pages 612--617. Naples, Italy.
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[2020ACTI4859] - Khamassi, M. (2020). Adaptive coordination of multiple learning strategies in brains and robots.
C. Mart ́ın-Vide et al. (Eds.) Proceedings of the 9th International Conference on the Theory and Practice of Natural Computing - LNCS 12494, Springer-Verlag, publisher. Pages 3-22. Taoyuan, Taiwan. Invited paper.
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[2020AP4820] - Doncieux, S. and Bredèche, N. and LeGoff, L. and Girard, B. and Coninx, A. and Sigaud, O. and Khamassi, M. and Díaz-Rodríguez, N. and Filliat, D. and Hospedales, T. and Eiben, A. and Duro, R. (2020). DREAM Architecture: a Developmental Approach to Open-Ended Learning in Robotics.
Published : HAL preprint..
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[2019ACLI4691] - Genzel, L. and Schut, E. and Schröder, T. and Eichler, R. and Khamassi, M. and Gomez, A. and Lobato, I. and Battaglia, F.P. (2019). The object space task shows cumulative memory expression in both mice and rats.
PLoS Biology. Vol 17 No 6 Pages e3000322.
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[2019ACLI4693] - Cinotti, F.* and Fresno, V.* and Aklil, N. and Coutureau, E. and Girard, B. and Marchand, A.° and Khamassi, M.° (2019). Dopamine blockade impairs the exploration-exploitation trade-off in rats.
Scientific Reports. Vol 9 Pages 6770 (* equally contributing authors) (° equally contributing senior authors).
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[2019ACLI4715] - Cinotti, F. and Marchand, A. and Roesch, M.R. and Girard, B. and Khamassi, M. (2019). Impacts of inter-trial interval duration on a computational model of sign-tracking vs. goal-tracking behaviour.
Psychopharmacology. Vol 236 No 8 Pages 2373-2388.
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[2019ACLI4749] - Zaraki, A.* and Khamassi, M.* and Wood, L. and Lakatos, G. and Tzafestas, C. and Amirabdollahian, F. and Robins, B. and Dautenhahn, K. (2019). A Novel Reinforcement-Based Paradigm for Children to Teach the Humanoid Kaspar Robot.
International Journal of Social Robotics. Vol 12 No 3 Pages 709-720 (* equally contributing authors).
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[2019ACLN4720] - Khamassi, M. and Chatila, R. and Mille, A. (2019). Éthique et Sciences Cognitives.
Intellectica. Vol 2019/1 No 70 Pages 7-39.
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[2019COS4716] - Khamassi, M. and Decremps, F. (2019). 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. Pages -.
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[2019INVI4723] - Khamassi, M. (2019). Exploiting individual differences to inform computational models of dopamine in reinforcement learning.
BRAINCONF 2019, Bordeaux Neurocampus Conferences (Caillé-Garnier, S., Georges, F. and Trifilieff, P.). Bordeaux, France. invited conference.
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[2019INVI4724] - Khamassi, M. (2019). Hippocampal replays under the scrutiny of reinforcement learning models.
4th Quadrennial Meeting on OFC function (Schoenbaum, G., Gottfried, J., Murray, E., Khamassi, M. and Pessiglione, M.). Paris, France. invited conference.
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[2019INVI4725] - Khamassi, M. (2019). Online adaptive coordination of model-based and model-free reinforcement learning systems in the brain.
NeuroBridges 2019 Computational Neuroscience School (El Hady, A., Loewenstein, Y. and Hansel, D.). Cluny, France. invited conference.
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[2019INVI4726] - Khamassi, M. (2019). Online adaptive coordination of model-based and model-free reinforcement learning systems in the brain.
Barcelona Cognition Brain and Technologies Summerschool (Verschure, P., Prescott, T. and Mura, A.). Barcelona, Spain. invited conference.
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[2019INVI4825] - Khamassi, M. (2019). Hippocampal replay and preplay through the lenses of model-based reinforcement learning.
Hippocampal replay symposium (Benchenane, K., Girard, B., Khamassi, M.). Sorbonne Université, Paris, France. invited conference.
[ BIB ]

[2019ACTI4705] - Hadfield, J. and Chalvatzaki, G. and Koutras, P. and Khamassi, M. and Tzafestas, C. and Maragos, P. (2019). A Deep Learning Approach for Multi-View Engagement Estimation of Children in a Child-Robot Joint Attention Task.
Proceedings of the 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2019). Pages -. Macau, China.
[ BIB ]

[2019ACTI4731] - Gillepsie, J. and Rano, I. and Siddique, N.H. and Santos, J.A. and Khamassi, M. (2019). Using Reinforcement Learning to Attenuate for Stochasticity in Robot Navigation Controllers.
Proceedings of the 2019 IEEE Symposium Series on Computational Intelligence (SSCI 2019). Pages -. Xiamen, China.
[ BIB ]

[2019COM4698] - Cinotti, F. and Girard, B. and Khamassi, M. (2019). Variability and regulation of reinforcement learning processes in rats.
UKNeuralComp19. Nottingham, UK. Poster.
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[2018ACLI4498] - Viejo, G. and Girard, B. and Procyk, E. and Khamassi, M. (2018). Adaptive coordination of working-memory and reinforcement learning in non-human primates performing a trial-and-error problem solving task.
Behavioural Brain Research. Vol 355 Pages 76-89.
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[2018ACLI4510] - Aklil, N. and Girard, B. and Denoyer, L. and Khamassi, M. (2018). Sequential action selection and active sensing for budgeted localization in robot navigation.
International Journal of Semantic Computing. Vol 12 No 1 Pages 109--127.
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[2018ACLI4572] - Dollé, L. and Chavarriaga, R. and Guillot, A.* and Khamassi, M.* (2018). Interactions of spatial strategies producing generalization gradient and blocking: a computational approach.
PLoS Computational Biology. Vol 14 No 4 Pages e1006092 (* equally contributing authors).
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[2018ACLI4582] - Khamassi, M. and Velentzas, G. and Tsitsimis, T. and Tzafestas, C. (2018). 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. Vol 10 No 4 Pages 881-893.
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[2018ACLI4599] - Chatila,R. and Renaudo, E. and Andries, M. and Chavez Garcia, R.O. and Luce-Vayrac, P. and Gottstein, R. and Alami, R. and Clodic, A. and Devin, S. and Girard, B. and Khamassi, M. (2018). Towards Self-Aware Robots.
Frontiers in Robotics and AI. Vol 5 Pages 88.
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[2018ACLI4600] - Velentzas, G. and Tsitsimis, T. and Rano, I. and Tzafestas, C. and Khamassi, M. (2018). Adaptive reinforcement learning with active state-specific exploration for engagement maximization during simulated child-robot interaction.
Paladyn Journal of Behavioral Robotics. Vol 9 Pages 235-253.
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[2018ACLI4620] - Lee, B. and Gentry, R. and Bissonette, G.B. and Herman, R.J. and Mallon, J.J. and Bryden, D.W. and Calu, D.J. and Schoenbaum, G. and Coutureau, E. and Marchand, A. and Khamassi, M. and Roesch, M.R. (2018). Manipulating the revision of reward value during the intertrial interval increases sign tracking and dopamine releases.
PLoS Biology. Vol 16 No 9 Pages e2004015.
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[2018ACLI4621] - Bavard, S. and Lebreton, M. and Khamassi, M. and Coricelli, G. and Palminteri, S. (2018). Reference point and range-adaptation produce both rational and irrational choices in human reinforcement learning.
Nature Communications. Vol 9 No 1 Pages 4503.
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[2018ACLI4648] - Cazé, R.* and Khamassi, M.* and Aubin, L. and Girard, B. (2018). Hippocampal replays under the scrutiny of reinforcement learning models.
Journal of Neurophysiology. Vol 120 Pages 2877-2896 (* equally contributing authors).
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[2018COS4520] - Khamassi, M. and Pacherie, E. (2018). Action.
Collins, T., Andler, D. and Tallon-Baudry, C. (Eds.) La cognition : du neurone à la société, Paris, France: Gallimard, publisher.
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[2018INVI4522] - Khamassi, M. (2018). A computational account of the role of dopamine in model-free learning and exploration modulation.
EBPS Computational Psychiatry Workshop (Flagel, S.B. and Paulus, M.). University of Cambridge, UK. invited conference.
[ BIB ]

[2018INVI4654] - Khamassi, M. (2018). Hippocampal replays under the scrutiny of reinforcement learning models.
6th International Meeting on Computational Properties of the Prefrontal Cortex (Schall, J. and Womelsdorf, T.). Vanderbilt University, Nashville, Tennessee, USA. invited conference.
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[2018INVI4655] - Khamassi, M. (2018). Robot learning for adaptive child-robot interaction.
Ethical dialogues for developing socially responsible robots for children with autism (Richardson, K.). DeMonfort University, Leicester, UK. invited conference.
[ BIB ]

[2018INVI4656] - Khamassi, M. (2018). Hippocampal replays under the scrutiny of reinforcement learning models.
Workshop on Latest Advances in Complex Spatial Navigation in Animals, Computational Models and Neuro-inspired Robots (Dominey, P.F., Fellous, J.M. and Weitzenfeld, A.). Lyon, France. invited conference.
[ BIB ]

[2018INVI4657] - Khamassi, M. (2018). Meta-learning processes involving the medial prefrontal cortex.
Mini Symposium on Frontiers in medial prefrontal cortex research (Coutureau, E., Marchand, A. and Procyk, A.). Bordeaux, France. invited conference.
[ BIB ]

[2018INVN4824] - Khamassi, M. (2018). Is it efficient to perform meta-learning with social rewards the same way as with non-social ones? Insights from robotics experiments.
Decision-making mini-symposium (Palminteri, S.). Ecole Normale Supérieure, Paris, France. invited conference.
[ BIB ]

[2018ACTI4562] - Aubin, L. and Khamassi, M. and Girard, B. (2018). Prioritized Sweeping Neural DynaQ with Multiple Predecessors, and Hippocampal Replays .
Living Machines 2018. Vol 10928 Pages 16-27. Paris, France. https://arxiv.org/abs/1802.05594.
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[2018ACTI4577] - Pasala, S. and Khamassi, M. and Pammi, V.S.C. (2018). Geometric features that describe reference frames in forming intuitive landmarks during spatial navigation.
Proceedings of Seventh International Conference on Spatial Cognition (ICSC 2018). Pages in press. Rome, Italy.
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[2018ACTI4604] - Khamassi, M. and Chalvatzaki, G. and Tsitsimis, T. and Velentzas, G. and Tzafestas, C. (2018). A framework for robot learning during child-robot interaction with human engagement as reward signal.
Proceedings of the 27th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN 2018). Pages 461-464. Nanjing City Prize for Best Late Breaking Report.
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[2018COM4585] - Cinotti, F. and Fresno, V. and Aklil, N. and Coutureau, E. and Girard, B. and Marchand, A. and Khamassi, M. (2018). Dopamine regulation of the exploration-exploitation trade-off in rats.
Eighth International Symposium on Biology of Decision Making (SBDM 2018). Paris, France. poster # 17.
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[2018COM4586] - Aubin, L. and Khamassi, M. and Girard, B. (2018). Prioritized Sweeping Neural DynaQ with Multiple Predecessors, and Hippocampal Replays.
Learning and decision-making at the interface between Neuroscience, Artificial Intelligence and Robotics workshop.. Paris, France. Satellite workshop of SBDM2018.
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[2018COM4606] - Khamassi, M. and Chalvatzaki, G. and Tsitsimis, T. and Velentzas, G. and Tzafestas, C. (2018). An extended framework for robot learning during child-robot interaction with human engagement as reward signal.
BAILAR workshop at the 27th International Symposium on Robot and Human Interactive Communication (RO-MAN 2018). Nanjing, China.
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[2018COM4607] - Zaraki, A. and Khamassi, M. and Wood, L. and Lakatos, G. and Tzafestas, C. and Robins, B. and Dautenhahn, K. (2018). A Novel Paradigm for Children as Teachers to the Kaspar Robot Learner.
BAILAR workshop at the 27th International Symposium on Robot and Human Interactive Communication (RO-MAN 2018). Nanjing, China.
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[2018COM4653] - Grynszpan, O. and Mouquet, E. and Rushworth, M. and Sallet, J. and Khamassi, M. (2018). Computational model of the user's learning process when cued by a social versus non-social agent.
Late Breaking Poster at the 6th annual International Conference on Human-Agent Interaction (HAI 2018). Southampton, UK.
[ BIB ]

[2018AP4672] - Cinotti, F. and Fresno, V. and Aklil, N. and Coutureau, E. and Girard, B. and Marchand, A. and Khamassi, M. (2018). Dopamine regulates the exploration-exploitation trade-off in rats.
Published : bioRxiv preprint..
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[2017ACLI4466] - Rougier, N.P. and Hinsen, K. and Alexandre, F. and Arildsen, T. and Barba, L. and Benureau, F.C.Y. and Brown, C.T. and de Buyl, P. and Caglayan, O. and Davison, A.P. and Delsuc, M.A. and Detorakis, G. and Diem, A.K. and Drix, D. and Enel, P. and Girard, B. and Guest, O. and Hall, M.G. and Henriques, R.N. and Hinaut, X. and Jaron, K.S. and Khamassi, M. and Klein, A. and Manninen, T. and Marchesi, P. and McGlinn, D. and Metzner, C. and Petchey, O.L. and Plesser, H.E. and Poisot, T. and Ram, K. and Ram, Y. and Roesch, E. and Rossant, C. and Rostami, V. and Shifman, A. and Stachelek, J. and Stimberg, M. and Stollmeier, F. and Vaggi, F. and Viejo, G. and Vitay, J. and Vostinar, A. and Yurchak, R. and Zito, T. (2017). Sustainable computational science: the ReScience initiative.
PeerJ Computer Science. Vol 3 Pages e142.
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[2017INVI3817] - Khamassi, M. (2017). A computational model of parallel learning processes involved in Pavlovian lever-autoshaping.
50th Winter Conference on Brain Research (WCBR). Big Sky, Montana, USA. invited conference.
[ BIB ]

[2017INVN4015] - Khamassi, M. (2017). A computational account of the role of dopamine in model-free learning and exploration modulation.
NeuroFrance 2017 French Neuroscience Society. Bordeaux, France. invited conference.
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[2017ACTI3860] - Khamassi, M. and Velentzas, G. and Tsitsimis, T. and Tzafestas, C. (2017). Active exploration and parameterized reinforcement learning applied to a simulated human-robot interaction task.
IEEE Robotic Computing 2017. Pages 28-35. Taipei, Taiwan.
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[2017ACTI3861] - Aklil, N. and Girard, B. and Khamassi, M. and Denoyer, L. (2017). Sequential Action Selection for Budgeted Localization in Robots.
IEEE Robotic Computing 2017. Pages -. Taipei, Taiwan.
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[2017ACTI3863] - Velentzas, G. and Tzafestas, C. and Khamassi, M. (2017). Bio-inspired meta-learning for active exploration during non-stationary multi-armed bandit tasks.
IEEE Intelligent Systems Conference 2017. Pages -. London, UK.
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[2017ACTI3864] - Rano, I. and Khamassi, M. and Wong-Lin, K. (2017). A Drift Diffusion Model of Biological Source Seeking for Mobile Robots.
IEEE ICRA 2017. Pages -. Singapore.
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[2017ACTI3980] - Velentzas, G. and Tzafestas, C. and Khamassi, M. (2017). Bridging Computational Neuroscience and Machine Learning on Non-Stationary Multi-Armed Bandits.
Third Multidisciplinary Conference on Reinforcement Learning and Decision Making. Pages extended abstract. Ann Arbor, Michigan.
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[2017ACTI3981] - Cinotti, F. and Fresno, V. and Aklil, N. and Coutureau, E. and Girard, B. and Marchand, A. and Khamassi, M. (2017). Dopamine enables dynamic regulations of exploration.
Third Multidisciplinary Conference on Reinforcement Learning and Decision Making. Pages extended abstract. Ann Arbor, Michigan.
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[2017ACTI3997] - Gillepsie, J. and Rano, I. and Siddique, N. and Santos, J.A. and Khamassi, M. (2017). Reinforcement Learning for Bio-Inspired Target Seeking.
TAROS 2017 Conference. Springer. Pages -. Guildford, Surrey, UK.
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[2017COM4027] - Cinotti, F. and Fresno, V. and Aklil, N. and Coutureau, E. and Girard, B. and Marchand, A. and Khamassi, M. (2017). Dopamine enables dynamic regulation of exploration.
Seventh International Symposium on Biology of Decision Making (SBDM 2017). Bordeaux, France. poster.
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[2017COM4467] - Tsitsimis, T. and Velentzas, G. and Khamassi, M. and Tzafestas, C. (2017). Online adaptation to human engagement perturbations in simulated human-robot interaction using hybrid reinforcement learning.
MultiLearn workshop at the 25th European Signal Processing Conference. Kos Island, Greece.
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[2017COM4476] - Cazé, R. and Khamassi, M. and Doncieux, S. and Girard, B. (2017). The exclusive-or: a key for the reliable propagation of synchronous activity in the hippocampus?.
Integrated Systems Neuroscience 2017 meeting. Manchester, UK. poster.
[ BIB ]


[2016ACLI3623] - Viejo, G. and Girard, B. and Khamassi, M. (2016). [Re] Speed/accuracy trade-off between the habitual and the goal-directed process .
ReScience. Vol 2 No 1 Pages NA.
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[2016ACLN3683] - Khamassi, M. and Girard, B. and Clodic, A. and Devin, S. and Renaudo, E. and Pacherie, E. and Alami, R. and Chatila, R. (2016). Integration of Action, Joint Action and Learning in Robot Cognitive Architectures.
Intellectica. Vol 2016/1 No 65 Pages 169-203.
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[2016ACLN3722] - Khamassi, M. and Doncieux, S. (2016). Nouvelles approches en Robotique Cognitive.
Intellectica. Vol 2016/1 No 65 Pages 7-25.
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[2016ACLN3723] - Girard, B. and Khamassi, M. (2016). Coopération de systèmes d’apprentissage par renforcement multiples.
Techniques de l'Ingénieur, Editions T.I., publisher. Vol 42622210 No s7793 Pages 1-16.
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[2016COV3672] - Khamassi, M. and Decremps, F. (2016). De l’art de conjuguer esprit critique et démarche scientifique.
The Conversation, The Conversation, publisher.
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[2016COV4578] - Khamassi, M. and Chatila, R. (2016). La conscience d'une machine.
Interstices, INRIA, publisher. Revue de culture scientifique en ligne publiée par Inria.
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[2016INVI3441] - Khamassi, M. (2016). A computational account of the role of dopamine in model-free learning and exploration modulation.
''Addiction, in theory'' meeting (Dayan, P. and Niv, Y. and Schoenbaum, G.). Gatsby Unit, University College London, London, UK. invited conference.
[ BIB ]

[2016INVI3449] - Khamassi, M. (2016). Coordination of adaptive working-memory and reinforcement learning in human and non-human primates.
Sixth International Symposium on Motivational and Cognitive Control (Brown, V. and O'Connell, R. and O'Neill, M. and Sallet, J.). University of Saint Andrews, Scotland, UK. invited conference.
[ BIB ]

[2016INVI3625] - Khamassi, M. (2016). A computational account of the role of dopamine in model-free learning and exploration modulation.
Sixth International Symposium on Biology of Decision-Making (Boraud, T. and Doya, K. and Khamassi, M. and Koechlin, E. and Pessiglione, M.). Paris, France. invited conference.
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[2016INVI3628] - Khamassi, M. (2016). Coordination of adaptive working-memory and reinforcement learning in human and non-human primates.
Fifth International Meeting on Computational Properties of Prefrontal Cortex (Procyk, E. and Averbeck, B. and Durstewitz, D. and Euston, D. and Holroyd, C. and Laubach, M. and Seamans J.). Lyon, France. invited conference.
[ BIB ]

[2016ACTI3695] - Pasala, S.K. and Khamassi, M. and Pammi, V.S.C. (2016). Variation in Intuitive Geometric Construct of Spatial Perception during Navigation.
Proceedings of the International Conference of the Academy of Neuroscience for Architecture (ANFA 2016). Pages -. Salk Institute, La Jolla, CA, USA.
[ BIB ]

[2016COM3814] - Cinotti, F. and Fresno, V. and Aklil, N. and Coutureau, E. and Girard, B. and Marchand, A. and Khamassi, M. (2016). Dopamine blockade affects exploration but not learning rate in a non-stationary 3-armed bandit task .
Sixth Symposium on Biology of Decision Making (SBDM 2016). Paris, France.
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[2016AP4470] - Khamassi, M. and Tzafestas, C. (2016). Active exploration in parameterized reinforcement learning.
Published : arXiv preprint..
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[2015ACLI3082] - Khamassi, M. and Quilodran, R. and Enel, P. and Dominey, P.F. and Procyk, E. (2015). Behavioral regulation and the modulation of information coding in the lateral prefrontal and cingulate cortex.
Cerebral Cortex. Vol 25 No 9 Pages 3197-3218.
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[2015ACLI3134] - Lesaint, F. and Sigaud, O. and Clark, J.J. and Flagel, S.B. and Khamassi, M. (2015). Experimental predictions drawn from a computational model of sign-trackers and goal-trackers.
Journal of Physiology - Paris. Vol 109 No 1-3 Pages 78-86.
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[2015ACLI3495] - Palminteri, S. and Khamassi, M. and Joffily, M. and Coricelli, G. (2015). Contextual modulation of value signals in reward and punishment learning.
Nature Communications. Vol 6 Pages 2015/08/25/online.
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[2015ACLI3543] - Viejo, G. and Khamassi, M. and Brovelli, A. and Girard, B. (2015). Modelling choice and reaction time during arbitrary visuomotor learning through the coordination of adaptive working memory and reinforcement learning.
Frontiers in Behavioral Neuroscience. Vol 9 Pages 225.
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[2015ACLN3577] - de Loor, P. and Mille, A. and Khamassi, M. (2015). Intelligence artificielle : l’apport des paradigmes incarnés.
Intellectica. Vol 2015/2 No 64 Pages 27-52.
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[2015COV3412] - Khamassi, M. and Chatila, R. (2015). La conscience d’une machine.
Dossier Pour la Science. Pages Les Robots en quête d'humanité.
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[2015INVI3442] - Khamassi, M. (2015). Dual-system reinforcement learning and dopamine-independent Pavlovian goal-tracking behaviors.
NeuroBridges Workshop (El Hady, A. and Mongillo, G. and Lowenstein, Y.). Université Paris Descartes, Paris, France. invited conference.
[ BIB ]

[2015INVI3496] - Khamassi, M. (2015). Some applications of the model-based / model-free reinforcement learning framework to Neuroscience & Robotics.
Third International Conference on Cognition, Brain and Computation (Miyapuram, K. and Lahiri, U. and Manjaly, J. and Mutha, P. and Sunny, M.). Ahmedabad, India. invited conference (plenary).
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[2015INVI3578] - Khamassi, M. (2015). Some applications of the model-based / model-free reinforcement learning framework to Neuroscience & Robotics.
International Conference on Cognition in Smart Cities (Pasala, S.K. et al.). Vishakhapatnam, India. invited conference (keynote).
[ BIB ]

[2015INVI3609] - Khamassi, M. (2015). Some applications of the model-based / model-free reinforcement learning framework to Neuroscience & Robotics.
International Conference on Computational Intelligence (Rao, A.A. et al.). Visakhapatnam, India. invited conference (keynote).
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[2015INVN3443] - Khamassi, M. (2015). Medial prefrontal cortex (dACC) and the adaptive regulation of reinforcement learning parameters: neurophysiology, computational model and some robotic implementations.
First Computational Neuroscience Symposium at UPMC (Delord, B. and Faure, P. and Girard, B. and Lambert, R. and Rondi-Reig, L.). Université Pierre et Marie Curie, Paris, France. invited conference.
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[2015INVN3444] - Khamassi, M. (2015). Some applications of the model-based / model-free reinforcement learning framework to Neuroscience and Robotics.
Computational Neuroscience Seminars (Ostojic, S.). Ecole Normale Supérieure Ulm, Paris, France. invited conference.
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[2015ACTI3559] - Renaudo, E and Girard, B. and Chatila, R and Khamassi, M. (2015). Respective advantages and disadvantages of model-based and model-free reinforcement learning in a robotics neuro-inspired cognitive architecture.
Biologically Inspired Cognitive Architectures BICA 2015. Vol 71 Pages 178-184. Lyon, France.
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[2015ACTI3502] - Renaudo, E. and Girard, B. and Chatila, R. and Khamassi, M. (2015). Which criteria for autonomously shifting between goal-directed and habitual behaviors in robots?.
5th International Conference on Development and Learning and on Epigenetic Robotics (ICDL-EPIROB). Pages 254-260. Providence, RI, USA.
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[2015COM3340] - Liénard, J. and Bellot, J. and Cos, I. and Khamassi, M. and Girard, B. (2015). Transmission delays in the basal ganglia proper are sufficient to explain beta-band oscillations in Parkinson's disease: mean-field and reduced models.
Workshop on Neural Population Dynamics. Gif-sur-Yvette, France. abstract & poster.
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[2015COM3413] - Wydoodt, P. and Sescousse, G. and Domenech, P. and Barbalat, G. and Khamassi, M. and Dreher, J.-C. (2015). Gambler’s fallacy and hot hand fallacy in pathological gamblers.
Fifth Symposium on Biology of Decision Making (SBDM 2015). Paris, France. Poster.
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[2015COM3414] - Marchand, A. and Fresno, V. and Aklil, N. and Cinotti, F. and Girard, B. and Khamassi, M. and Coutureau, E. (2015). Striatal dopamine controls exploration in a probabilistic task.
Fifth Symposium on Biology of Decision Making (SBDM 2015). Paris, France. Poster.
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[2015COM3415] - Griessinger, T. and Khamassi, M. and Coricelli, G. (2015). A behavioral investigation of inter-individual differences in learning during repeated strategic interactions.
Fifth Symposium on Biology of Decision Making (SBDM 2015). Paris, France. Poster.
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[2015COM3416] - Girard, B. and Aklil, N. and Cinotti, F. and Fresno, V. and Denoyer, L. and Coutureau, E. and Khamassi, M. and Marchand, A. (2015). Modelling rat learning behavior under uncertainty in a non-stationary multi-armed bandit task.
Colloque de la Société des Neurosciences Françaises. Montpellier, France. Poster.
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[2015COM3417] - Viejo, G. and Khamassi, M. and Brovelli, A. and Girard, B. (2015). Modelling choice and reaction time during instrumental learning through the coordination of adaptive working-memory and reinforcement learning.
Colloque de la Société des Neurosciences Françaises. Montpellier, France. Poster.
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[2015COM3503] - Renaudo, E. and Devin, S. and Girard, B. and Chatila, R. and Alami, R. and Khamassi, M. and Clodic, A. (2015). Learning to interact with humans using goal-directed and habitual behaviors.
Workshop on Learning for Human-Robot Collaboration at RO-MAN 2015 Conference. Kobe, Japan.
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[2015COM3576] - Larsen, T. and Palminteri, S. and Vidal, J.R. and Khamassi, M. and Joffily, M. and Coricelli, G. (2015). Context can induce seeking behaviour in punishment conditions.
Poster at the 13th Annual Meeting of the Society for NeuroEconomics. Miami, USA.
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[2014ACLI3188] - Lesaint, F. and Sigaud, O. and Khamassi, M. (2014). Accounting for Negative Automaintenance in Pigeons: A Dual Learning Systems Approach and Factored Representations.
PLoS ONE. Vol 9 No 10 Pages e111050.
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[2014ACLI3016] - Lesaint, F. and Sigaud, O. and Flagel, S.B. and Robinson, T.E. and Khamassi, M. (2014). Modelling Individual Differences in the Form of Pavlovian Conditioned Approach Responses: A Dual Learning Systems Approach with Factored Representations.
PLoS Computational Biology. Vol 10 No 2 Pages e1003466.
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[2014INVI3445] - Khamassi, M. (2014). Dorsal anterior cingulate cortex and the adaptive regulation of reinforcement learning parameters: neurophysiology, model and robotic implementation.
Symposium at International Cognitive Neuroscience Conference (Holroyd, C.). Brisbane, Australia. invited conference.
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[2014ACTI3089] - Renaudo, E. and Girard, B. and Chatila, R. and Khamassi, M. (2014). Design of a control architecture for habit learning in robots.
Biomimetic & Biohybrid Systems, Third International Conference, Living Machines 2014. Vol 8608 Pages 249--260.
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[2014COM3139] - Viejo, G. and Khamassi, M. and Brovelli, A. and Girard, B. (2014). Modelling choice and reaction time during instrumental learning through the coordination of adaptive working memory and reinforcement learning.
Fourth Symposium on Biology of Decision Making (SBDM 2014). Paris. Poster.
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[2014COM3140] - Aklil, N. and Marchand, A. and Fresno, V. and Coutureau, E. and Denoyer, L. and Girard, B. and Khamassi, M. (2014). Modelling rat learning behavior under uncertainty in a non-stationary multi-armed bandit task.
Fourth Symposium on Biology of Decision Making (SBDM 2014). Paris. Poster.
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[2014COM3154] - Viejo, G. and Khamassi, M. and Brovelli, A. and Girard, B. (2014). Coordination of adaptive working memory and reinforcement learning systems explaining choice and reaction time in a human experiment.
Twenty Third Annual Computational Neuroscience Meeting: CNS*2014 BMC Neuroscience. Vol 15 No Suppl. 1 Pages P156. Quebec City, Canada. abstract & poster.
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[2014COM3234] - Bellot, J. and Liénard, J. and Khamassi, M. and Girard, B. (2014). Investigation of the effect of different dopaminergic levels on the basal ganglia action selection properties using a biologically constrained computational model.
Society for Neuroscience Annual Meeting. Washington, DC, USA. poster 555.23/TT42.
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[2014COM3418] - Lesaint, F. and Sigaud, O. and Khamassi, M. (2014). A model of negative automaintenance in pigeons: Dual learning and factored representations.
Society for Neuroscience Annual Meeting. Washington, DC, USA. Poster.
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[2014COM3419] - Lesaint, F. and Sigaud, O. and Khamassi, M. (2014). Accounting for negative automaintenance in pigeons: A dual learning systems approach and factored representations.
Fourth Symposium on Biology of Decision Making (SBDM 2014). Paris, France. Poster.
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[2014COM3420] - Marchand, A. and Fresno, V. and Khamassi, M. and Coutureau, E. (2014). Dopaminergic modulation of the exploration level in a non-stationary probabilistic task.
FENS Meeting. Milan, Italy. Poster.
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[2014THDR3090] - Khamassi, M. (2014). Coordination of parallel learning processes in animals and robots.
. Paris, France. HDR. Université Pierre et Marie Curie - Paris 6.
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[2013ACLI2538] - Khamassi, M. and Enel, P. and Dominey P.F. and Procyk, E. (2013). Medial prefrontal cortex and the adaptive regulation of reinforcement learning parameters.
Progress in Brain Research. Vol 202 Pages 441-464.
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[2013ACLI2907] * - Arleo, A. and Déjean, C. and Allegraud, P. and Khamassi, M. and Zugaro, M.B. and Wiener, S.I. (2013). Optic flow stimuli update anterodorsal thalamus head direction neuronal activity in rats.
Journal of Neuroscience. Vol 33 No 42 Pages 16790-16795.
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[2013ACLI2888] - Cos, I and Khamassi, M.* and Girard, B (2013). Modeling the Learning of Biomechanics and Visual Planning for Decision-Making of Motor Actions.
Journal of Physiology - Paris. Vol 107 No 5 Pages 399-408 (* corresponding author).
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[2013INVI3448] - Khamassi, M. (2013). Dual-system reinforcement learning and dopamine-independent Pavlovian goal-tracking behaviors.
International Motivational and Cognitive Control Meeting (Bouret, S. and Laubach, M. and Sallet, J.). ICM, Paris, France. invited conference.
[ BIB ]

[2013INVI3454] - Khamassi, M. (2013). Reinforcement learning models and dopamine signaling in the basal ganglia.
Harvard Summer Program in Trento (Coricelli, G.). University of Trento, Italy. invited conference.
[ BIB ]

[2013INVN3446] - Khamassi, M. (2013). Apprentissage par renforcement : de la modélisation des processus neuraux aux applications robotiques.
Brain & Language Research Institute (Hannagan, T.). Avignon, France. invited conference.
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[2013INVN3447] - Khamassi, M. (2013). Table ronde.
Forum des Sciences Cognitives (Cognivence, FRESCO). Cloître des Cordeliers, Paris, France. invited conference.
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[2013COM2852] - Khamassi, M. and Bellot, J. and Sigaud, O. and Girard, B. (2013). Which temporal difference learning algorithm best reproduces dopamine activity in multi-choice task?.
11th meeting of the French Neuroscience Society. Lyon-Grenoble, France. poster P2.214.
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[2013COM2868] - Bellot, J and Sigaud, O. and Girard, B. and Khamassi, M. (2013). Which temporal difference learning algorithm best reproduces dopamine activity in multi-choice task?.
Third Symposium on Biology of Decision Making (SBDM 2013). Paris. Poster #5.
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[2013COM2882] - Bellot, J. and Khamassi, M. and Sigaud, O. and Girard, B. (2013). Which Temporal Difference learning algorithm best reproduces dopamine activity in a multi-choice task?.
Twenty Second Annual Computational Neuroscience Meeting: CNS*2013. Paris, France. poster P144.
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[2013COM2975] - Lesaint, F. and Sigaud, O. and Flagel, S. and Robinson, T. and Khamassi, M. (2013). Modelling individual differences in rats using a dual learning systems approach and factored representations.
First International Interdisciplinary Reinforcement Learning and Decision Making Conference Princeton University. Princeton, USA. Poster.
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[2013COM2976] - Lesaint, F. and Sigaud, O. and Khamassi, M. (2013). Modelling individual differences observed in rats using a dual learning systems approach and factored representations.
Third Symposium on Biology of Decision Making (SBDM 2013). Paris, France. Poster.
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[2013COM2977] - Lesaint, F. and Sigaud, O. and Flagel, S. and Robinson, T. and Khamassi, M. (2013). Modelling individual differences in rats using a dual learning systems approach and factored representations.
Fifth International Motivational and Cognitive Control Meeting. ICM Paris.
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[2013COM3421] - Palminteri, S. and Khamassi, M. and Joffily, M. and Coricelli, G. (2013). Reinforcement learning and counterfactual outcomes: evidence for context-value dependent adjustment of action values.
Society for Neuroeconomics Annual Meeting. Lausanne, Switzerland. Poster.
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[2013COM3422] - Humphries, M.D. and Khamassi, M. and Gurney, K. (2013). Dopaminergic control of the exploration-exploitation trade-off via the basal ganglia.
Third Symposium on Biology of Decision Making (SBDM 2013). Paris, France. Poster.
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[2012ACLI2192] - Humphries, M. and Khamassi, M. and Gurney, K. (2012). Dopaminergic control of the exploration-exploitation trade-off via the basal ganglia.
Frontiers in Neuroscience. Vol 6:9 Pages 1-14.
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[2012ACLI2232] - Caluwaerts, K. and Staffa, M. and N'Guyen, S. and Grand, C. and Dollé, L. and Favre-Felix, A. and Girard, B. and Khamassi, M. (2012). A biologically inspired meta-control navigation system for the Psikharpax rat robot.
Bioinspiration & Biomimetics. Vol 7(2):025009 Pages 1-29.
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[2012ACLI2724] - Khamassi, M. and Humphries, M. D. (2012). Integrating cortico-limbic-basal ganglia architectures for learning model-based and model-free navigation strategies.
Frontiers in Behavioral Neuroscience. Vol 6:79 Pages 1-19.
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[2012COV4579] - Dumas, G. and Khamassi, M. and N'Diaye, K. and Foubert, L. and Jouffe, Y. and Roth, C. (2012). La publicitié peut avoir des effets nocifs sur la société.
“Tribune” (Opinion) in LeMonde.fr, LeMonde, publisher.
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[2012INVI3453] - Khamassi, M. (2012). Reinforcement learning for Cognitive Robotics: Models and links with biology.
Neuromorphic Engineering Summerschool (Etienne-Cummings, R. and Horiuchi, T. and Delbruck, T.). Telluride, Colorado, USA. invited conference.
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[2012INVN3451] - Khamassi, M. (2012). Reinforcement learning models and dopamine signaling in the basal ganglia.
Troisième Colloque du GDR Multi-Electrodes (Riehle, A. and Bénard, C. and Chavane, F. and Hok, V. and Iherti, T. and Kilavic, B. and Pourpe, C. and Ravel, S. and Sargolini, F. and Save, E.). Institut des Neurosciences de la Timone, Marseille, France. invited conference.
[ BIB ]

[2012INVN3452] - Khamassi, M. (2012). The Actor-Critic model and dopamine signals in the basal ganglia.
Basal Ganglia Days (Pessiglione, M.). ICM, Paris, France. invited conference.
[ BIB ]

[2012ACTI2399] - Bellot, J. and Sigaud, O. and Khamassi, M. (2012). Which Temporal Difference Learning algorithm best reproduces dopamine activity in a multi-choice task?.
From Animals to Animats: Proceedings of the Twelfth International Conference on Adaptive Behaviour (SAB 2012), Ziemke, T., Balkenius, C., Hallam, J. (Eds), Springer, publisher. Vol 7426/2012 Pages 289-298. Odense, Denmark. BEST PAPER AWARD.
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[2012ACTI2393] - Caluwaerts, K. and Favre-Felix, A. and Staffa, M. and N'Guyen, S. and Grand, C. and Girard, B. and Khamassi, M. (2012). Neuro-inspired navigation strategies shifting for robots: Integration of a multiple landmark taxon strategy.
Living Machines 2012, Lecture Notes in Artificial Intelligence, Prescott, T.J. et al. (Eds.). Vol 7375/2012 Pages 62-73. Barcelona, Spain.
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[2012ACTN2684] - Bellot, J. and Sigaud, O. and Roesch, M. R. and Schoenbaum, G. and Girard, B and Khamassi, M. (2012). Dopamine neurons activity in a multi-choice task: reward prediction error or value function?.
Proceedings of the French Computational Neuroscience NeuroComp/KEOpS\'12 workshop. Pages 1-7. Bordeaux, France.
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[2012COM2403] - Caluwaerts, K. and Staffa, M. and N'Guyen, S. and Grand, C. and Dollé, L. and Favre-Félix, A. and Girard, B. and Khamassi, M. (2012). A biologically inspired meta-control navigation system for the Psikharpax rat robot.
Second Symposium on Biology of Decision Making (SBDM 2012). Paris, France. Poster.
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[2012COM3423] - Bellot, J. and Sigaud, O. and Khamassi, M. (2012). Which Temporal Difference Learning algorithm best reproduces dopamine activity in a multi-choice task?.
Fourth Robotics and Neuroscience Days. Paris, France. Poster.
[ BIB ]

[2012COM3424] - Bellot, J. and Sigaud, O. and Khamassi, M. (2012). Which Temporal Difference Learning algorithm best reproduces dopamine activity in a multi-choice task?.
Second Symposium on Biology of Decision Making (SBDM 2012). Paris, France. Poster.
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[2012COM3425] - Khamassi, M. and Lallée, S. and Enel, P. and Procyk, E. and Dominey P.F. (2012). Robot cognitive control with a neurophysiologically inspired reinforcement learning model.
Second Symposium on Biology of Decision Making (SBDM 2012). Paris, France. Poster.
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[2012COM3426] - Humphries, M.D. and Khamassi, M. and Gurney, K. (2012). Dopaminergic control of the exploration-exploitation trade-off via the basal ganglia.
FENS Meeting. Barcelona, Spain. Poster.
[ BIB ]


[2011ACLI1994] - Khamassi, M. and Lallée, S. and Enel, P. and Procyk, E. and Dominey, P.F. (2011). Robot cognitive control with a neurophysiologically inspired reinforcement learning model.
Frontiers in Neurorobotics. Vol 5:1 Pages 1-14.
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[2011COS1838] - Khamassi, M. and Wilson, C. and Rothé, R. and Quilodran, R. and Dominey, P.F. and Procyk, E. (2011). Meta-learning, cognitive control, and physiological interactions between medial and lateral prefrontal cortex.
Mars, R.B., Sallet, J., Rushworth, M.B. and Yeung, N. (Eds) Neural Basis of Motivational and Cognitive Control, Cambridge, MA: MIT Press, publisher. Pages 351-370.
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[2011COV1852] - Khamassi, M. (2011). Psikharpax, le robot-rat intelligent.
Futura Sciences. Pages 1-22. In both French and English.
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[2011INVI3455] - Khamassi, M. (2011). Regulation of exploration and exploitation in the prefrontal cortex: neurophysiology, model and robotic implementation.
International Conference on Decision Making (Singh, A.K. and Srinivasan, N. and Kar, B.R. and Mishra, R.K. and Chandrasekhar Pammi, V.S.). Allahabad, India. invited conference.
[ BIB ]

[2011COM1875] - Khamassi, M. and Lallée, S. and Enel, P. and Procyk, E. and Dominey P.F. (2011). Gestion de l'incertitude dans le monde réel avec un modèle d'apprentissage par renforcement neuro-inspiré.
Journées Nationales de la Recherche en Robotique Humanoïde. Toulouse, France. Oral presentation.
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[2011COM1876] - Khamassi, M. and Lallée, S. and Enel, P. and Procyk, E. and Dominey P.F. (2011). Human- Robot Interaction with the iCub Humanoid Robot using a Neuro-Inspired Model of Reinforcement Learning.
International workshop on bio-inspired robots. Nantes, France.
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[2011COM1877] - Caluwaerts, K. and Grand, C. and N'Guyen, S. and Dollé, L. and Guillot, A. and Khamassi, M. (2011). Design of a biologically inspired navigation system for the Psikharpax rodent robot.
International workshop on bio-inspired robots. Nantes, France. Poster.
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[2010ACLI1569] - Benchenane, K. and Peyrache, A. and Khamassi, M. and Tierney, P.I. and Gioanni, Y. and Battaglia, F.P. and Wiener, S.I. (2010). Coherent theta oscillations and reorganization of spike timing in the hippocampal-prefrontal network upon learning.
Neuron. Vol 66 No 6 Pages 921-936.
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[2010ACLI1570] - Peyrache, A. and Benchenane, K. and Khamassi, M. and Wiener, S.I. and Battaglia, F.P. (2010). Sequential reinstatement of neocortical activity during slow oscillations depends on cells' intrinsic excitability.
Frontiers in Systems Neuroscience. Vol 3:18 Pages 1-7.
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[2010ACLI1571] - Peyrache, A. and Benchenane, K. and Khamassi, M. and Wiener, S.I. and Battaglia, F.P. (2010). Principal component analysis of ensemble recordings reveals cell assemblies at high temporal resolution.
Journal of Computational Neuroscience. Vol 29 No 1-2 Pages 309-325.
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[2010INVI3456] * - Khamassi, M. (2010). Integration of reinforcement learning and task monitoring in the prefrontal cortex.
Computational Approaches to Cognitive Function (Gutkin, B.S.). Ecole Normale Supérieure Ulm, Paris, France. invited conference.
[ BIB ]

[2010ACTI1573] * - Khamassi, M. and Quilodran, R. and Enel, P. and Procyk, E. and Dominey, P.F. (2010). A model of integration between reinforcement learning and task monitoring in the prefrontal cortex.
From animals to animats: Proceedings of the Eleventh International Conference on Simulation of Adaptive Behavior (SAB2010), Springer Verlag LNAI 6226, publisher. Pages 424-434.
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[2010ACTN1640] * - Khamassi, M. and Quilodran, R. and Enel, P. and Dominey P.F. and Procyk, E. (2010). Role of the frontal cortex in solving the exploration-exploitation trade-off.
Proceedings of the Fifth French Conference on Computational Neuroscience, Berlin, Heidelberg: Springer-Verlag, publisher. Pages 191-194. Lyon, France. ISBN:978-2-9532965-1-8.
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[2010ACTN2238] * - Enel, P. and Khamassi, M. and Procyk, E. and Dominey, P.F. (2010). Reinforcement learning model in probalistically rewarded task.
Proceedings of the Fifth French Conference on Computational Neuroscience. Pages 185-190. Lyon, France. ISBN:978-2-9532965-1-8.
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[2010COM1574] * - Benchenane, K. and Peyrache, A. and Khamassi, M. and Wiener, S.I. and Battaglia, F.P. (2010). Coherent oscillations and learning-related reorganization of spike timing.
Proceedings of the Fourth International Conference on Cognitive Systems, CogSys10. ETH Zurich, Switzerland.
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[2009ACLI1572] - Peyrache, A. and Khamassi, M. and Benchenane, K. and Wiener, S.I. and Battaglia, F.P. (2009). Replay of rule-learning related neural patterns in the prefrontal cortex during sleep.
Nature Neuroscience. Vol 12 No 7 Pages 919-926.
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[2009ACTI3427] * - Benchenane, K. and Peyrache, A. and Khamassi, M. and Wiener, S.I. and Battaglia, F.P. (2009). Coherence of Theta Rhythm between Hippocampus and Medial Prefrontal Cortex Modulates Prefrontal Network Activity During Learning in Rats.
Conference abstract in Frontiers in Systems Neuroscience Journal: 12th Meeting of the Hungarian Neuroscience Society. Pages Abstract. Budapest, Hungary.
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[2009COM3428] * - Khamassi, M. and Quilodran, R. and Procyk, E. and Dominey P.F. (2009). Anterior Cingulate Cortex integrates reinforcement learning and task-monitoring: evidence from computational modelling, neural network simulation and primate neurophysiology.
Society for Neuroscience Annual Meeting. Chicago, IL, USA. Poster.
[ BIB ]


[2008ACLI932] - Khamassi, M.* and Mulder, A.B.* and Tabuchi, E. and Douchamps, V. and Wiener S.I. (2008). Anticipatory reward signals in ventral striatal neurons of behaving rats.
European Journal of Neuroscience. Vol 28 No 9 Pages 1849-1866 (* equally contributing authors).
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[2008COS935] - Battaglia, F.P. and Peyrache, A. and Khamassi, M. and Wiener S.I. (2008). Spatial decisions and neuronal activity in hippocampal projection zones in prefrontal cortex and striatum.
Mizumori, S.J.Y. (Ed.) Hippocampal place fields: Relevance to learning and memory, Oxford University Press, publisher. Pages 289-309.
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[2008INVI3458] - Khamassi, M. (2008). Actor-Critic models: from ventral striatal reward-related activity to robotics simulations of rat behaviour.
Okinawa Institute of Science and Technology (Doya, K.). Okinawa, Japan. invited conference.
[ BIB ]

[2008INVN3457] - Khamassi, M. (2008). Actor-Critic models: from ventral striatal reward-related activity to robotics simulations of rat behaviour.
Colloque du GDR Neurosciences de la Mémoire (Laroche, S.). Aussois, France. invited conference.
[ BIB ]

[2008ACTI839] - Dollé, L. and Khamassi, M. and Girard, B. and Guillot, A. and Chavarriaga, R. (2008). Analyzing interactions between navigation strategies using a computational model of action selection.
Spatial Cognition VI. Learning, Reasoning, and Talking about Space, Berlin, Heidelberg: Springer-Verlag, publisher. Pages 71-86.
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[2008ACTI3429] * - Benchenane, K. and Peyrache, A. and Khamassi, M. and Wiener, S.I. and Battaglia, F.P. (2008). Theta Band LFP Coherence Between Hippocampus And Prefrontal Cortex and Reorganization of Ensemble Cell Activity During Learning.
Conference Abstract in Neuropsychobiology Journal. Vol 58(3-4) Pages 233. Abstract.
[ BIB ]


[2007INVN3459] - Khamassi, M. (2007). Actor-Critic models: from ventral striatal reward-related activity to robotics simulations.
Third day in Computational Neuroscience (Deneve, S.). Collège de France, Paris, France. invited conference.
[ BIB ]

[2007ACTI934] * - Battaglia, F.P. and Benchenane, K. and Khamassi, M. and Peyrache, A. and Wiener, S.I. (2007). Neural ensembles and local field potentials in the hippocampoprefrontal cortex system during spatial learning and strategy shifts in rats.
Advances in Cognitive Neurodynamics: Proceedings of the First International Conference on Cognitive Neurodynamics (ICCN), Springer, publisher. Vol 2-09-0003 Pages 1-4. Shanghai, China.
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[2007COM3430] * - Khamassi, M. and Mulder, A.B. and Tabuchi, E. and Douchamps, V. and Wiener S.I. (2007). Actor-Critic models of reward prediction signals in the rat ventral striatum require multiple input modules.
Society for Neuroscience Annual Meeting. San Diego, CA, USA. Poster.
[ BIB ]

[2007COM3431] * - Peyrache, A. and Benchenane, K. and Khamassi, M. and Douchamps, V. and Tierney, P.L. and Battaglia, F.P. and Wiener, S.I. (2007). Rat medial prefrontal cortex neurons are modulated by both hippocampal theta rhythm and sharp waveripple events.
Society for Neuroscience Annual Meeting. San Diego, CA, USA. Poster.
[ BIB ]

[2007COM3432] * - Benchenane, K. and Peyrache, A. and Khamassi, M. and Tierney, P.L. and Douchamps, V. and Battaglia, F.P. and Wiener, S.I. (2007). Increased firing rate and theta modulation in medial prefrontal neurons during episodes of high coherence in the theta band of hippocampal/prefrontal local field potentials (LFP) in behaving rats.
Society for Neuroscience Annual Meeting. San Diego, CA, USA. Poster.
[ BIB ]

[2007COM3433] * - Battaglia, F.P. and Peyrache, A. and Benchenane, K. and Khamassi, M. and Douchamps, V. and Tierney, P.L. and Wiener, S.I. (2007). Rat medial prefrontal cortex neurons are modulated by both hippocampal theta rhythm and sharp waveripple events.
Society for Neuroscience Annual Meeting. San Diego, CA, USA. Poster.
[ BIB ]

[2007COM3434] * - Khamassi, M. and Battaglia, F.P. and Peyrache, A. and Douchamps, V. and Tierney, P. and Wiener S.I. (2007). Transitions in behaviorally correlated activity in medial prefrontal neurons of rats acquiring and switching strategies in a y-maze.
Okinawa Computational Neuroscience Workshop. Okinawa, Japan. Poster.
[ BIB ]

[2007THDR178] - Khamassi, M. (2007). Complementary roles of the rat prefrontal cortex and striatum in reward-based learning and shifting navigation strategies.
. Paris, France. These de doctorat. Université Pierre et Marie Curie, Paris 6.
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[2006INVI3460] - Khamassi, M. (2006). Concurrent and parallel neuromimetic learning systems for navigation.
ICEA European project workshop (Prescott, T.J.). Derby, UK. invited conference.
[ BIB ]

[2006ACTI427] - Khamassi, M. and Martinet, L.-E. and Guillot, A. (2006). Combining Self-Organizing Maps with Mixture of Experts: Application to an Actor-Critic Model of Reinforcement Learning in the Basal Ganglia.
From Animals to Animats 9 (SAB 2006), Berlin, Heidelberg: Springer-Verlag, publisher. Pages 394-405.
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[2006COM351] - Dollé, L. and Khamassi, M. and Guillot, A. and Chavarriaga, R. (2006). Coordination of learning modules for competing navigation strategies into different mazes.
Poster presented at Workshop Parallel memory systems for spatial cognition. Rome, Italy.
[ BIB ]

[2006COM3435] * - Battaglia, F.P. and Khamassi, M. and Peyrache, A. and Douchamps, V. and Tierney, P. and Wiener, S.I. (2006). Spatial and reward correlates in medial prefrontal neurons of rats acquiring and switching strategies in a y-maze.
Society for Neuroscience Annual Meeting. Atlanta, GA, USA. Poster.
[ BIB ]

[2006COM3436] * - Wiener, S.I. and Khamassi, M. and Peyrache, A. and Douchamps, V. and Tierney, P. and Battaglia, F.P. (2006). Transitions in behaviorally correlated activity in medial prefrontal neurons of rats acquiring and switching strategies in a y-maze.
Society for Neuroscience Annual Meeting. Atlanta, GA, USA. Poster.
[ BIB ]


[2005ACLI426] - Khamassi, M. and Lachèze, L. and Girard, B. and Berthoz, A. and Guillot, A. (2005). Actor-Critic Models of Reinforcement Learning in the Basal Ganglia: From Natural to Artificial Rats.
Adaptive Behavior. Vol 13 No 2 Pages 131-148.
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[2005ACLI457] - Meyer, J.-A. and Guillot, A. and Girard, B. and Khamassi, M. and Pirim, P. and Berthoz, A. (2005). The Psikharpax Project: Towards Building an Artificial Rat.
Robotics and Autonomous Systems. Vol 50 No 4 Pages 211-223.
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[2005COM3437] * - Battaglia, F.P. and Khamassi, M. and Douchamps, V. and Tierney, P.L. and Wiener, S.I. (2005). EEG correlations between hippocampus and prefrontal portex in rats performing a decision-making spatial task.
Society for Neuroscience Annual Meeting. Washington, DC, USA. Poster.
[ BIB ]

[2005COM3438] * - Mulder, A.B. and Tabuchi, E. and Khamassi, M. and Wiener S.I. (2005). Reward site associated activity in the ventral striatum of behaving rats.
Society for Neuroscience Annual Meeting. Washington, DC, USA. Poster.
[ BIB ]


[2004ACLI933] * - Zugaro, M. B. and Arleo, A. and Déjean, C. and Burguière, E. and Khamassi, M. and Wiener, S. I. (2004). Rat anterodorsal thalamic head direction neurons depend upon dynamic visual signals to select anchoring landmark cues.
European Journal of Neuroscience. Vol 20 No 2 Pages 530-536.
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[2004ACTI371] - Filliat, D. and Girard, B. and Guillot, A. and Khamassi, M. and Lachèze, L. and Meyer, J.-A. (2004). State of the artificial rat Psikharpax.
From Animals to Animats 8: Proceedings of the Seventh International Conference on Simulation of Adaptive Behavior, MIT Press, publisher. Pages 3-12. Cambridge, MA.
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[2004ACTI424] - Khamassi, M. and Girard, B. and Berthoz, A. and Guillot, A. (2004). Comparing three Critic Models of Reinforcement Learning in the Basal Ganglia Connected to a Detailed Actor in a S-R Task.
Proceedings of the Eighth International Conference on Intelligent Autonomous Systems, IOS Press, publisher. Pages 430-437. Amsterdam, The Netherlands.
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[2004ACTI3439] * - Arleo, A. and Déjean, C. and Boucheny, C. and Khamassi, M. and Zugaro, M.B. and Wiener, S.I. (2004). Optic field flow signals update the activity of head direction cells in the rat anterodorsal thalamus.
Abstract in Journal of Vestibular Research. Vol 14(2-3) Pages P095. Abstract.
[ BIB ]

[2004COM3440] * - Wiener, S.I. and Arleo, A. and Déjean, C. and Boucheny, C. and Khamassi, M. and Zugaro, M.B. (2004). Optic field flow signals update the activity of head direction cells in the rat anterodorsal thalamus.
Society for Neuroscience Annual Meeting. San Diego, CA, USA. Poster.
[ BIB ]


[2003COM425] - Khamassi, M. and Girard, B. and Guillot, A. and Berthoz, A. (2003). Mécanismes neuromimétiques d'apprentissage par renforcement dans l'architecture de contrôle du rat artificiel Psikharpax.
Poster presented at the french conference on artificial learning (CAp) within the frame of the AFIA platform, 1-4 july 2003. Laval, France.
[ BIB ]

[2003AP948] - Khamassi, M. (2003). Un modèle d'apprentissage par renforcement dans une architecture de contrôle de la sélection de l'action chez le rat artificiel Psikharpax.
. M.Sc. thesis, Cognitive Science. Université Pierre et marie Curie.
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