Nicolas Perrin-Gilbert
13
Documents
Présentation
Je suis roboticien et chercheur en apprentissage automatique.
Je travaille comme chargé de recherche au CNRS à l'ISIR (https://www.isir.upmc.fr/?lang=en), un laboratoire de Sorbonne Université à Paris, France.
Mots clés : *apprentissage automatique, apprentissage par renforcement, apprentissage de représentation, planification de mouvement, contrôle, locomotion à pattes, robots à pattes*.
Liens : [ISIR](https://www.isir.upmc.fr/personnel/perrin/ "ISIR") / [Github](https://github.com/perrin-isir "Github") / [DBLP](https://dblp.org/pid/37/1452.html "DBLP") / [Google Scholar](https://scholar.google.com/citations?user=_UceE6YAAAAJ&hl=fr "Google Scholar") / [Videos](https://www.youtube.com/channel/UC9incxmKuvpvWWfCIQbQq1A/videos "Videos")
I am a roboticist and machine learning researcher.
I work as a permanent CNRS research scientist (*chargé de recherche*) at [ISIR](https://www.isir.upmc.fr/?lang=en), a laboratory of Sorbonne University in Paris, France.
Key words: *machine learning, reinforcement learning, representation learning, motion planning, control, legged locomotion, legged robots*.
Links: [ISIR](https://www.isir.upmc.fr/personnel/perrin/ "ISIR") / [Github](https://github.com/perrin-isir "Github") / [DBLP](https://dblp.org/pid/37/1452.html "DBLP") / [Google Scholar](https://scholar.google.com/citations?user=_UceE6YAAAAJ&hl=fr "Google Scholar") / [Videos](https://www.youtube.com/channel/UC9incxmKuvpvWWfCIQbQq1A/videos "Videos")
Publications
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Exploratory State Representation LearningFrontiers in Robotics and AI, 2022, 9, ⟨10.3389/frobt.2022.762051⟩
Article dans une revue
hal-03864236v1
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The Quality-Diversity Transformer: Generating Behavior-Conditioned Trajectories with Decision TransformersGECCO '23: Genetic and Evolutionary Computation Conference, Jul 2023, Lisbon Portugal, France. pp.1221-1229, ⟨10.1145/3583131.3590433⟩
Communication dans un congrès
hal-04237993v1
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Divide & Conquer Imitation Learning2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2022), Oct 2022, Kyoto, Japan. pp.8630-8637, ⟨10.1109/IROS47612.2022.9982020⟩
Communication dans un congrès
hal-03753530v1
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Assessing Quality-Diversity Neuro-Evolution Algorithms Performance in Hard Exploration ProblemsGECCO 2022 Workshop on Quality Diversity Algorithm Benchmarks, Jul 2022, Boston (MA), United States
Communication dans un congrès
hal-04237990v1
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Diversity policy gradient for sample efficient quality-diversity optimizationGECCO '22: Genetic and Evolutionary Computation Conference, Jul 2022, Boston, United States. pp.1075-1083, ⟨10.1145/3512290.3528845⟩
Communication dans un congrès
hal-03864262v1
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Selection-Expansion: A Unifying Framework for Motion-Planning and Diversity Search Algorithms30th International Conference on Artificial Neural Networks - ICANN 2021, Sep 2021, Bratislava, Slovakia. pp.568-579, ⟨10.1007/978-3-030-86380-7_46⟩
Communication dans un congrès
hal-03404366v1
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First-Order and Second-Order Variants of the Gradient Descent in a Unified Framework30th International Conference on Artificial Neural Networks - ICANN 2021, Sep 2021, Bratislava, Slovakia. pp.197-208, ⟨10.1007/978-3-030-86340-1_16⟩
Communication dans un congrès
hal-03404369v1
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Understanding Failures of Deterministic Actor-Critic with Continuous Action Spaces and Sparse RewardsArtificial Neural Networks and Machine Learning – ICANN 2020, Sep 2020, Bratislava, Slovakia. pp.308-320, ⟨10.1007/978-3-030-61616-8_25⟩
Communication dans un congrès
hal-03080925v1
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State Representation Learning from Demonstration6th International Conference on Machine Learning, Optimization, and Data Science, LOD 2020, Jul 2020, Siena, Italy
Communication dans un congrès
hal-03083156v1
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PBCS: Efficient Exploration and Exploitation Using a Synergy Between Reinforcement Learning and Motion PlanningArtificial Neural Networks and Machine Learning – ICANN 2020, Sep 2020, Bratislava, Slovakia. pp.295-307, ⟨10.1007/978-3-030-61616-8_24⟩
Communication dans un congrès
hal-03080918v1
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Learning Compositional Neural Programs with Recursive Tree Search and PlanningAdvances in Neural Information Processing Systems 32 (NeurIPS 2019), Dec 2019, Vancouver, Canada
Communication dans un congrès
hal-03080949v1
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QD-RL: Efficient Mixing of Quality and Diversity in Reinforcement Learning2020
Pré-publication, Document de travail
hal-03083159v1
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Learning Compositional Neural Programs for Continuous Control2020
Pré-publication, Document de travail
hal-03083161v1
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