This page is outdated, refer to the ISIR website for up-to-date information.

Research topics / Thèmes de Recherche

Neuromimetic models for neuroscience and autonomous robotics.

• Action Selection. What are the action sequences to be selected to ensure survival, the success of the execution of a task? Which motivation, among a set of conflicting motivations, has to be prioritized in a given context? Which goals to choose? How to adapt these decisions to an unknown and dynamic environment?
• Navigation strategies. When goals have been selected, how to reach them? Which navigation strategies should we use in order to optimize various constraints, such as computational load, energy consumption, uncertainty about the outcome? do we have to choose one strategy at a time or fuse the suggestions provided by various strategies?
• Motor execution. How to encode the sensorimotor space so as to act efficiently? Which reference frame should we use? How to calibrate the effectore whithout an external supervisor? How to control action? How to anticipate in order to compensate for delays and interact with a dynamic environment?

Modèles neuromimétiques pour les neurosciences et la robotique autonome.

• Sélection de l'action. Quelles successions d'actions mettre en œuvre pour assurer la survie, le succès de l'exécution d'une tâche ? Quelle motivation, parmi un ensemble de motivations conflictuelles, mettre en avant dans un contexte donné ? Quels buts choisir ? Comment adapter ces décisions à un environnement dynamique et inconnu a priori ?
• Stratégies de navigation. Les buts ayant été identifiés, comment les atteindre physiquement ? Quelles stratégies de navigation utiliser afin d'optimiser au mieux diverses contraintes telles que la charge computationnelle, l'énergie dépensée, l'incertitude du résultat ? Une seule stratégie doit-elle être sélectionnée ou la décision doit-elle être le résultat d'une combinaison de plusieurs stratégies ?
• Execution motrice. Comment encoder l'espace sensorimoteur pour agir efficacement ? Quels référentiels favoriser ? Comment (re-)calibrer les effecteurs en l'absence de superviseur ? Comment contrôler l'action ? Comment anticiper pour compenser les retards et interagir avec un environnement dynamique ?

Resume / C.V.

My resume in french as of January 2009.

Mon CV, mise à jour de janvier 2009.

Publications

Refereed Journals / Journaux à comité de lecture

2009

F. Colas, F. Flacher, T. Tanner, P. Bessière, and B. Girard (2009). Bayesian models of eye movement selection with retinotopic maps. Biological Cybernetics, 100(3):203-214. [doi:10.1007/s00422-009-0292-y]

2008

Girard, B., Tabareau, N., Pham, Q.C., Berthoz, A. and Slotine, J.-J. (2008). Where neuroscience and dynamic system theory meet autonomous robotics: a contracting basal ganglia model for action selection. Neural Networks, 21(4):628-641. [preprint pdf | doi:10.1016/j.neunet.2008.03.009]

2007

Tabareau, N., Bennequin, D., Berthoz, A., Slotine, J.-J. and Girard, B. (2007). Geometry of the superior colliculus mapping and efficient oculomotor computation. Biological Cybernetics, 97(4):279-292. [preprint pdf | doi:10.1007/s00422-007-0172-2]

2005

Girard, B., Berthoz, A. (2005). From brainstem to cortex: computational models of the saccade generation circuitry. Progress in Neurobiology. 77(4):215-251.[preprint pdf | doi:10.1016/j.pneurobio.2005.11.001 | journal]

Girard, B., Filliat, D., Meyer, J.-A., Berthoz, A., and Guillot, A. (2005). Integration of navigation and action selection functionalities in a computational model of cortico-basal ganglia-thalamo-cortical loops. Adaptive Behavior, Special Issue on Artificial Rodents. 13(2):115-130 [preprint pdf | doi:10.1177/105971230501300204]

Khamassi, M., Lachèze, L., Girard, B., Berthoz, A., and Guillot, A. (2005). Actor-critic models of reinforcement learning in the basal ganglia: From natural to artificial rats. Adaptive Behavior, Special Issue on Artificial Rodents. 13(2):131-148. [preprint pdf | doi:10.1177/105971230501300205]

Meyer, J.-A., Guillot, A., Girard, B., Khamassi, M., Pirim, P., and Berthoz, A. (2005). The Psikharpax project: Towards building an artificial rat. Robotics and Autonomous Systems, 50(4):211-223. [preprint pdf | doi:10.1016/j.robot.2004.09.018]

2003

Girard, B., Cuzin, V., Guillot, A., Gurney, K., and Prescott, T. (2003). A basal ganglia inspired model of action selection evaluated in a robotic survival task. Journal of Integrative Neuroscience, 2(3):179-200. [preprint pdf | doi:10.1142/S0219635203000299]

2001

Girard, B., Robert, G., and Guillot, A. (2001). Jeux vidéo et intelligence artificielle située (paper in french). In Cognito, 22:57-72. [preprint pdf]

Refereed Conferences and Workshops / Conférences et Workshops à comité de lecture

2010

J.-B. Mouret, S. Doncieux and B. Girard (2010). Importing the Computational Neuroscience Toolbox into Neuro-Evolution-Application to Basal Ganglia. GECCO'10: Proceedings of the 12th annual conference on Genetic and evolutionary computation, ACM. [pdf]

S. N'Guyen, P. Pirim, J.-A. Meyer and B. Girard (2010). An Integrated Neuromimetic Model of the Saccadic Eye Movements for the Psikharpax Robot. From animals to animats 11. Proceedings of the Eleventh International Conference on Simulation of Adaptive Behavior, Springer.

J. Liénard, A. Guillot and B. Girard (2010). Multi-Objective Evolutionary Algorithms to Investigate Neurocomputational Issues : The Case Study of Basal Ganglia Models. From animals to animats 11. Proceedings of the Eleventh International Conference on Simulation of Adaptive Behavior, Springer.

L. Dollé, D. Sheynikhovich, B. Girard, B. Ujfalussy, R. Chavariagga and A. Guillot (2010). Analyzing interactions between cue-guided and place-based navigation with a computational model of action selection: Influence of sensory cues and training. From animals to animats 11. Proceedings of the Eleventh International Conference on Simulation of Adaptive Behavior, Springer.

2009

M.-T. Tran, P. Souères, M. Taïx and B. Girard (2009). Eye-centered vs body-centered reaching control: A robotics insight into the neuroscience debate. Robotics and Biomimetics (ROBIO 2009)

C. Masson and B. Girard (2009). Decoding the Grid Cells for Metric Navigation Using the Residue Numeral System. 2nd International Conference on Cognitive Neurodynamics (ICCN2009).[pdf]

2008

A. Coninx, A. Guillot, B. Girard (2008). Adaptive motivation in a biomimetic action selection mechanism. In Daucé, E., Perrinet, L. (Eds) NeuroComp 2008, pages 158-162.[pdf]

F. Colas, F. Flacher, P. Bessière, B. Girard (2008). Explicit uncertainty for eye movement selection. In Daucé, E., Perrinet, L. (Eds) NeuroComp 2008, pages 103-107.[pdf]

L. Dollé, M. Khamassi, B. Girard, A. Guillot and R. Chavarriaga (2008). Analyzing interactions between navigation strategies using a computational model of action selection. In Spatial Cognition 2008, pages 71-86. Lecture Notes in Computer Science, Springer.[pdf]

2006

Manfredi, L., Maini, E., Laschi, C., Dario, P., Girard, B., Tabareau, N. and Berthoz, A. (2006). Implementation of a neurophysiologic model of saccadic movements on an anthropomorphic robotic head. In IEEE-RAS Int. Conf. on Humanoid Robots, pages 438-443. [website]

Girard, B., Tabareau, N., Berthoz, A. and Slotine, J.-J. (2006). Selective amplification using a contracting model of the basal ganglia. In Alexandre, F., Boniface, Y., Bougrain, L., Girau, B. and Rougier, N. (Eds) NeuroComp 2006, pages 30-33. [pdf | website]

2005

Girard, B., Tabareau, N., Slotine, J.-J. and Berthoz, A. (2005). Contracting model of the basal ganglia. In Bryson, J., Prescott, T. and Seth, A. (Eds) Modelling Natural Action Selection: Proceedings of an International Workshop, pages 69-76. AISB Press, Brighton, UK. [pdf]

2004

Filliat, D., Girard, B., Guillot, A., Khamassi, M., Lachèze, L., and Meyer, J.-A. (2004). State of the artificial rat Psikharpax. In Schaal, S., Ijspeert, A., Billard, A., Vijayakumar, S., Hallam, J., and Meyer, J.-A., editors, From Animals to Animats 8: Proceedings of the Seventh International Conference on Simulation of Adaptive Behavior, pages 3-12. MIT Press, Cambridge, MA. [pdf]

Girard, B., Filliat, D., Meyer, J.-A., Berthoz, A., and Guillot, A. (2004). An integration of two control architectures of action selection and navigation inspired by neural circuits in the vertebrates: The basal ganglia. In Bowman, H. and Labiouse, C., editors, Connectionist Models of Cognition and Perception II, Proceedings of the Eighth Neural Computation and Psychology Workshop, pages 72-81. World Scientific, Singapore. [pdf]

Khamassi, M., Girard, B., 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. In Groen, F., Amato, N., Bonarini, A., Yoshida, E., and Kröse, B., editors, Proceedings of the Eighth International Conference on Intelligent Autonomous Systems, pages 430-437. IOS Press, Amsterdam, The Netherlands.

2002

Girard, B., Cuzin, V., Guillot, A., Gurney, K. N., and Prescott, T. J. (2002). Comparing a bio-inspired robot action selection mechanism with winner-takes-all. In Hallam, B., Floreano, D., Hallam, J., Hayes, G., and Meyer, J.-A., editors, From Animals to Animats 7. Proceedings of the Seventh International Conference on Simulation of Adaptive Behavior, pages 75-84. The MIT Press, Cambridge, MA. [ps.gz]

PhD Thesis (in French) / Thèse de Doctorat

Girard, B. (2003). Intégration de la navigation et de la sélection de l'action dans une architecture de contrôle inspirée des ganglions de la base. PhD thesis, LIP6/AnimatLab, Université Pierre et Marie Curie, Paris, France. Spécialité Informatique. [pdf]

Abstracts and Posters / Résumés et Posters

L. Dollé, D. Sheynikhovich, B. Girard, R. Chavarriaga and A. Guillot, (2009). A new computational model of switching between response-based and place-based navigation strategies. The 4th Computational Cognitive Neuroscience Conference (CCNC09). Boston, MA, USA. (poster).

M.-T. Tran, P. Souères, M. Taïx and B. Girard (2009) A computational approach from robotics for testing eye-centered vs body-centered reaching control. In Progress in Motor Control 2009, Marseille (Poster and Abstract).

B. Girard, N. Tabareau, D. Bennequin, J.-J. Slotine and A. Berthoz (2007). A mathematical proof of the coupling of the spatiotemporal transformation and the superior colliculus mapping. In SfN 2007, San Diego. (Slide session and abstract).

N. Tabareau, D. Bennequin, A. Berthoz, J.-J. Slotine and B. Girard (2007). The coupling of the superior colliculus mapping and the spatiotemporal transformation. In Delgado-Garcia, J.M. and Vidal, P.-P. (Eds.), Neural Bases of Motor Learning and Performance : From Cell to Function (satellite symposium of the 17th Annual Meeting of Neural Control of Movement), Carmona. (Invited conference and abstract).

Girard, B., Tabareau, N., Slotine, J.-J. and Berthoz, A. (2006). Using contraction analysis to design a model of the cortico-baso-thalamo-cortical loops. In Ijspeert, A.K., Buchli, J., Selverston, A., Rabinovitch, M., Hasler, M., Gerstner, W., Billard, A., Markram, H. and Floreano, D., editors, EPFL LATSIS Symposium 2006, Dynamical principles for neuroscience and intelligent biomimetic devices, pages 85-86. EPFL, Lausanne, Switzerland. (Poster and abstract). [abstract]

Khamassi M., Girard B., Guillot A. et Berthoz A. (2003). Mécanismes neuromimétiques d'apprentissage par renforcement dans l'architecture de contrôle du rat artificiel Psikharpax. AFIA (Association Française d'Intelligence Artificielle) meeting 2003. (Poster)

Laithier, S., Girard, B., Cuzin, V., Prescott, T.J. et Gurney, K.N. (2002). A vertebrate brain-inspired model of action selection: More than a winner-takes-all? In T.J. Prescott and B. Webb, editors, Robotics as Theoretical Biology Workshop. (Poster)