Home » Teams » Amac » Olivier Sigaud
  • Olivier Sigaud

  • Full Professor
  • Team: Amac
  • Office: 56-66 301
  • Email: olivier.sigaud@sorbonne-universite.fr
  • Phone:01.44.27.88.53
  • Addresse: ISIR, Campus Pierre et Marie Curie, 4 place Jussieu, BC173, 75005 Paris
  • Bio: Born in 1968. Engineer, Phd in Computer Science from Paris XI University (Orsay) in 1996, PhD in Philosophy from Paris I University in 2004. Employed at Dassault Aviation (aerospace company, St-Cloud) from 1995 to 2001. Then Assistant Professor and finally Professor at LIP6 then ISIR. Main research topics: reinforcement learning, learning for robotics, computational neurosciences of decision making in animals.

Publications

  • Vaynee Sungeelee, Antoine Loriette, Olivier Sigaud, Baptiste Caramiaux. Co-Apprentissage Humain-Machine: Cas d'Étude en Acquisition de Compétences Motrices. 34ème conférence Francophone sur l'Interaction Humain-Machine, Apr 2023, Troyes, France. ⟨hal-03992717⟩
  • Vaynee Sungeelee, Antoine Loriette, Olivier Sigaud, Baptiste Caramiaux. Co-Apprentissage Humain-Machine : Cas d’Étude en Acquisition de Compétences Motrices. 2023. ⟨hal-04014981⟩
  • Thomas Carta, Clément Romac, Thomas Wolf, Sylvain Lamprier, Olivier Sigaud, et al.. Grounding Large Language Models in Interactive Environments with Online Reinforcement Learning. International Conference on Machine Learning 2023, Jul 2023, Honololu, Hawaii, United States. ⟨hal-03970122v3⟩
  • Alexandre Chenu, Nicolas Perrin-Gilbert, Olivier Sigaud. Divide & Conquer Imitation Learning. 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2022), Oct 2022, Kyoto, Japan. pp.8630-8637, ⟨10.1109/IROS47612.2022.9982020⟩. ⟨hal-03753530⟩
  • Thomas Carta, Sylvain Lamprier, Pierre-Yves Oudeyer, Olivier Sigaud. EAGER: Asking and Answering Questions for Automatic Reward Shaping in Language-guided RL. NeurIPS 2022 - Thirty-sixth Conference on Neural Information Processing Systems, Nov 2022, Nouvelle-Orléans, United States. ⟨hal-03902423⟩
  • Hugo Caselles-Dupré, Olivier Sigaud, Mohamed Chetouani. Pragmatically Learning from Pedagogical Demonstrations in Multi-Goal Environments. Thirty-sixth Conference on Neural Information Processing Systems (NeurIPS 2022), Nov 2022, New Orleans, United States. ⟨hal-03828002⟩
  • Aloïs Pourchot, Kevin Bailly, Alexis Ducarouge, Olivier Sigaud. Neural Architecture Search for Fracture Classification. 29th IEEE International Conference on Image Processing (ICIP 2022), Oct 2022, Bordeaux, France. ⟨hal-03753702⟩
  • Ahmed Akakzia, Olivier Sigaud. LEARNING OBJECT-CENTERED AUTOTELIC BEHAVIORS WITH GRAPH NEURAL NETWORKS. Conference on Lifelong Learning Agents - CoLLAs 2022, Aug 2022, Montréal, Canada. ⟨hal-03753526⟩
  • Aloïs Pourchot, Kévin Bailly, Alexis Ducarouge, Olivier Sigaud. An extensive appraisal of weight-sharing on the NAS-Bench-101 benchmark. Neurocomputing, 2022, 498, pp.28-42. ⟨10.1016/j.neucom.2022.04.108⟩. ⟨hal-03706214⟩
  • Thomas Pierrot, Valentin Macé, Felix Chalumeau, Arthur Flajolet, Geoffrey Cideron, et al.. Diversity policy gradient for sample efficient quality-diversity optimization. GECCO '22: Genetic and Evolutionary Computation Conference, Jul 2022, Boston, United States. pp.1075-1083, ⟨10.1145/3512290.3528845⟩. ⟨hal-03864262⟩
  • Cédric Colas, Tristan Karch, Olivier Sigaud, Pierre-Yves Oudeyer. Autotelic Agents with Intrinsically Motivated Goal-Conditioned Reinforcement Learning: A Short Survey. Journal of Artificial Intelligence Research, 2022, 74, ⟨10.1613/jair.1.13554⟩. ⟨hal-03901771⟩
  • Thomas Pierrot, Valentin Macé, Felix Chalumeau, Arthur Flajolet, Geoffrey Cideron, et al.. DIVERSITY POLICY GRADIENT FOR SAMPLE EFFI-CIENT QUALITY-DIVERSITY OPTIMIZATION. Workshop on Agent Learning in Open-Endedness (ALOE) at ICLR 2022, 2022, virtual, Vatican City. ⟨hal-03753541⟩
  • Olivier Sigaud, Hugo Caselles-Dupré, Cédric Colas, Ahmed Akakzia, Pierre-Yves Oudeyer, et al.. Towards Teachable Autonomous Agents. 2021. ⟨hal-03364200⟩
  • Alexandre Chenu, Nicolas Perrin-Gilbert, Stéphane Doncieux, Olivier Sigaud. Selection-Expansion: A Unifying Framework for Motion-Planning and Diversity Search Algorithms. 30th International Conference on Artificial Neural Networks - ICANN 2021, Sep 2021, Bratislava, Slovakia. pp.568-579, ⟨10.1007/978-3-030-86380-7_46⟩. ⟨hal-03404366⟩
  • Thomas Pierrot, Nicolas Perrin-Gilbert, Olivier Sigaud. First-Order and Second-Order Variants of the Gradient Descent in a Unified Framework. 30th International Conference on Artificial Neural Networks - ICANN 2021, Sep 2021, Bratislava, Slovakia. pp.197-208, ⟨10.1007/978-3-030-86340-1_16⟩. ⟨hal-03404369⟩
  • Ahmed Akakzia, Cédric Colas, Pierre-Yves Oudeyer, Mohamed Chetouani, Olivier Sigaud. Grounding Language to Autonomously-Acquired Skills via Goal Generation. ICLR 2021 - Ninth International Conference on Learning Representation, May 2021, Vienna / Virtual, Austria. ⟨hal-03121146⟩
  • Anis Najar, Olivier Sigaud, Mohamed Chetouani. Teaching a Robot with Unlabeled Instructions: The TICS Architecture. AAMAS 2021, May 2021, London (virtual), United Kingdom. ⟨hal-03224574⟩
  • Alexandre Chenu, Nicolas Perrin-Gilbert, Stephane Doncieux, Olivier Sigaud. Selection-Expansion: A Unifying Framework for Motion-Planning and Diversity Search Algorithms. 2021. ⟨hal-03196479⟩
  • Cédric Colas, Ahmed Akakzia, Pierre-Yves Oudeyer, Mohamed Chetouani, Olivier Sigaud. Language-Conditioned Goal Generation: a New Approach to Language Grounding in RL. 2021. ⟨hal-03099887⟩
  • Cédric Colas, Tristan Karch, Olivier Sigaud, Pierre-Yves Oudeyer. Intrinsically Motivated Goal-Conditioned Reinforcement Learning: a Short Survey. 2021. ⟨hal-03099891⟩
  • Pierre Fournier, Cédric Colas, Mohamed Chetouani, Olivier Sigaud. CLIC: Curriculum Learning and Imitation for object Control in non-rewarding environments. IEEE Transactions on Cognitive and Developmental Systems, 2021, 13 (2), pp.239-248. ⟨10.1109/TCDS.2019.2933371⟩. ⟨hal-02370859⟩
  • Guillaume Matheron, Nicolas Perrin, Olivier Sigaud. PBCS: Efficient Exploration and Exploitation Using a Synergy Between Reinforcement Learning and Motion Planning. Artificial Neural Networks and Machine Learning – ICANN 2020, Sep 2020, Bratislava, Slovakia. pp.295-307, ⟨10.1007/978-3-030-61616-8_24⟩. ⟨hal-03080918⟩
  • Guillaume Matheron, Nicolas Perrin, Olivier Sigaud. Understanding Failures of Deterministic Actor-Critic with Continuous Action Spaces and Sparse Rewards. Artificial Neural Networks and Machine Learning – ICANN 2020, Sep 2020, Bratislava, Slovakia. pp.308-320, ⟨10.1007/978-3-030-61616-8_25⟩. ⟨hal-03080925⟩
  • Ryan Lober, Olivier Sigaud, Vincent Padois. Task Feasibility Maximization using Model-Free Policy Search and Model-Based Whole-Body Control. Frontiers in Robotics and AI, 2020, 7, ⟨10.3389/frobt.2020.00061⟩. ⟨hal-01620370v3⟩
  • Stephane Doncieux, Nicolas Bredeche, Léni Kenneth Le Goff, Benoît Girard, Alexandre Coninx, et al.. DREAM Architecture: a Developmental Approach to Open-Ended Learning in Robotics. 2020. ⟨hal-02562103⟩
  • Anis Najar, Olivier Sigaud, Mohamed Chetouani. Interactively shaping robot behaviour with unlabeled human instructions. Autonomous Agents and Multi-Agent Systems, 2020, 34 (2), ⟨10.1007/s10458-020-09459-6⟩. ⟨hal-02996137⟩
  • Marwen Belkaid, Elise Bousseyrol, Romain Durand-de Cuttoli, Malou Dongelmans, Etienne K Duranté, et al.. Mice adaptively generate choice variability in a deterministic task. Communications Biology, 2020, 3, pp.34. ⟨10.1038/s42003-020-0759-x⟩. ⟨hal-02485779⟩
  • Felix Rutard, Olivier Sigaud, Mohamed Chetouani. Tirl: enriching actor-critic RL with non-expert human teachers and a trust model. The 29th IEEE International Conference on Robot and Human Interactive Communication, RO-MAN, 2020, Napoli, Italy. ⟨hal-03124262⟩
  • Thomas Pierrot, Nicolas Perrin, Olivier Sigaud. First-order and second-order variants of the gradient descent in a unified framework. 2019. ⟨hal-02397757⟩
  • Aloïs Pourchot, Nicolas Perrin, Olivier Sigaud. Importance mixing: Improving sample reuse in evolutionary policy search methods. 2019. ⟨hal-02397754⟩
  • Marwen Belkaid, Jérémie Naudé, Philippe Faure, Olivier Sigaud. Modélisation des stratégies de génération de choix variables chez la souris. Conférence Nationale en Intelligence Artificielle, Jul 2019, Toulouse, France. ⟨hal-02328815⟩
  • Cédric Colas, Pierre Fournier, Olivier Sigaud, Mohamed Chetouani, Pierre-Yves Oudeyer. CURIOUS: Intrinsically Motivated Modular Multi-Goal Reinforcement Learning. ICML 2019 - Thirty-sixth International Conference on Machine Learning, Jun 2019, Long Beach, United States. ⟨hal-01934921v2⟩
  • Cédric Colas, Olivier Sigaud, Pierre-Yves Oudeyer. A Hitchhiker's Guide to Statistical Comparisons of Reinforcement Learning Algorithms. ICLR Worskhop on Reproducibility, May 2019, Nouvelle-Orléans, United States. ⟨hal-02369859⟩
  • Olivier Sigaud, Freek Stulp. Policy search in continuous action domains: An overview. Neural Networks, 2019, 113, pp.28-40. ⟨10.1016/j.neunet.2019.01.011⟩. ⟨hal-02182466⟩
  • Cédric Colas, Olivier Sigaud, Pierre-Yves Oudeyer. How Many Random Seeds? Statistical Power Analysis in Deep Reinforcement Learning Experiments. 2018. ⟨hal-01890154⟩
  • Cédric Colas, Olivier Sigaud, Pierre-Yves Oudeyer. GEP-PG: Decoupling Exploration and Exploitation in Deep Reinforcement Learning Algorithms. International Conference on Machine Learning (ICML), Jul 2018, Stockholm, Sweden. ⟨hal-01890151⟩
  • Alexandre Péré, Sébastien Forestier, Olivier Sigaud, Pierre-Yves Oudeyer. Unsupervised Learning of Goal Spaces for Intrinsically Motivated Goal Exploration. ICLR2018 - 6th International Conference on Learning Representations, Apr 2018, Vancouver, Canada. ⟨hal-01891758⟩
  • Stéphane Doncieux, David Filliat, Natalia Díaz-Rodríguez, Timothy Hospedales, Richard Duro, et al.. Open-Ended Learning: A Conceptual Framework Based on Representational Redescription. Frontiers in Neurorobotics, 2018, 12, pp.59. ⟨10.3389/fnbot.2018.00059⟩. ⟨hal-01889947⟩
  • Nicolas Lehir, Alban Laflaquière, Olivier Sigaud. Identification of invariant sensorimotor structures as a prerequisite for the discovery of objects. Frontiers in Robotics and AI, 2018, 5, pp.70. ⟨10.3389/frobt.2018.00070⟩. ⟨hal-03124279⟩
  • Pierre Fournier, Olivier Sigaud, Mohamed Chetouani. Combining artificial curiosity and tutor guidance for environment exploration. Workshop on Behavior Adaptation, Interaction and Learning for Assistive Robotics at IEEE RO-MAN 2017, Aug 2017, Lisbon, Portugal. ⟨hal-01581363⟩
  • Alexis Ducarouge, Olivier Sigaud. The Successor Representation as a model of behavioural flexibility. Journées Francophones sur la Planification, la Décision et l'Apprentissage pour la conduite de systèmes (JFPDA 2017), Jul 2017, Caen, France. ⟨hal-01576352⟩
  • Cédric Colas, Olivier Sigaud, Pierre-Yves Oudeyer. GEP-PG: Decoupling Exploration and Exploitation in Deep Reinforcement Learning Algorithms. Journées Francophones sur la Planification, la Décision et l'Apprentissage pour la conduite de systèmes (JFPDA 2018), Jul 2017, Nancy, France. ⟨hal-01840576⟩
  • Chenyang Zhao, Timothy Hospedales, Freek Stulp, Olivier Sigaud. Tensor based knowledge transfer across skill categories for robot control. International Joint Conference in Artificial Intelligence (IJCAI), 2017, Melbourne, Australia. pp.1-7, ⟨10.24963/ijcai.2017/484⟩. ⟨hal-03124263⟩
  • Luka Peternel, Olivier Sigaud, Jan Babič. Unifying Speed-Accuracy Trade-Off and Cost-Benefit Trade-Off in Human Reaching Movements. Frontiers in Human Neuroscience, 2017, 11, pp.615. ⟨10.3389/fnhum.2017.00615⟩. ⟨hal-01679624⟩
  • Francesco Romano, Gabriele Nava, Morteza Azad, Jernej Camernik, Stefano Dafarra, et al.. The CoDyCo Project achievements and beyond: Towards Human Aware Whole-body Controllers for Physical Human Robot Interaction. IEEE Robotics and Automation Letters, 2017, ⟨10.1109/LRA.2017.2768126⟩. ⟨hal-01620789⟩
  • Ryan Lober, Vincent Padois, Olivier Sigaud. Efficient Reinforcement Learning for Humanoid Whole-Body Control. IEEE-RAS International Conference on Humanoid Robots, Nov 2016, Cancun, Mexico. ⟨hal-01377831⟩
  • Olivier Sigaud, Alain Droniou. Towards Deep Developmental Learning. IEEE Transactions on Cognitive and Developmental Systems, 2016, 8 (2), pp.99-114. ⟨10.1109/TAMD.2015.2496248⟩. ⟨hal-01331799⟩
  • Olivier Sigaud, Clément Masson, David Filliat, Freek Stulp. Gated networks: an inventory. 2016. ⟨hal-01313601⟩
  • Anis Najar, Olivier Sigaud, Mohamed Chetouani. Training a robot with evaluative feedback and unlabeled guidance signals. RO-MAN, 2016, New York, United States. pp.261-266, ⟨10.1109/ROMAN.2016.7745140⟩. ⟨hal-03124264⟩
  • Anis Najar, Olivier Sigaud, Mohamed Chetouani. Social-Task Learning for HRI. International Conference on Social Robotics, Oct 2015, Paris, France. pp.472-481, ⟨10.1007/978-3-319-25554-5_47⟩. ⟨hal-02422990⟩