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Number of documents

41

link to my webpage


http://people.isir.upmc.fr/sigaud
http://people.isir.upmc.fr/sigaud/en


Journal articles11 documents

Conference papers19 documents

  • 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⟩
  • 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⟩
  • Thomas Pierrot, Guillaume Ligner, Scott Reed, Olivier Sigaud, Nicolas Perrin, et al.. Learning Compositional Neural Programs with Recursive Tree Search and Planning. Advances in Neural Information Processing Systems 32 (NeurIPS 2019), Dec 2019, Vancouver, Canada. ⟨hal-03080949⟩
  • 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⟩
  • 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⟩
  • Alain Droniou, Serena Ivaldi, Vincent Padois, Olivier Sigaud. Autonomous Online Learning of Velocity Kinematics on the iCub: a Comparative Study. IEEE/RSJ International Conference on Intelligent Robots and Systems, Oct 2012, Vilamoura, Portugal. To appear. ⟨hal-00719964⟩
  • Didier Marin, Olivier Sigaud. Towards fast and adaptive optimal control policies for robots: A direct policy search approach. Robotica 2012, 2012, Guimaraes, Portugal. pp.21-26. ⟨hal-00703755⟩
  • Alain Droniou, Serena Ivaldi, Olivier Sigaud. Comparaison expérimentale d'algorithmes de régression pour l'apprentissage de modèles cinématiques du robot humanoïde iCub. Conférence Francophone sur l'Apprentissage Automatique, May 2012, Nancy, France. pp.95-110. ⟨hal-00719977⟩
  • Alain Droniou, Serena Ivaldi, Patrick Stalph, Martin Butz, Olivier Sigaud. Learning Velocity Kinematics: Experimental Comparison of On-line Regression Algorithms. Robotica, Apr 2012, Guimaraes, Portugal. pp.15-20. ⟨hal-00719975⟩
  • Didier Marin, Olivier Sigaud. Reaching optimally over the workspace: a machine learning approach. The Fourth IEEE RAS/EMBS International Conference on Biomedical Robotics and Biomechatronics, Jun 2012, Roma, Italy. pp.1128-1133, ⟨10.1109/BioRob.2012.6290743⟩. ⟨hal-00743371⟩
  • Alain Droniou, Serena Ivaldi, Olivier Sigaud. Comparaison expérimentale d'algorithmes de régression pour l'apprentissage de modèles cinématiques du robot humanoïde iCub. Conférence Francophone sur l'Apprentissage Automatique - CAp 2012, Laurent Bougrain, May 2012, Nancy, France. 16 p. ⟨hal-00745471⟩
  • Jean Bellot, Olivier Sigaud, Mehdi Khamassi. Which Temporal Difference Learning algorithm best reproduces dopamine activity in a multi-choice task?. International Conference on Simulation of Adaptive Behaviour (SAB 2012), Aug 2012, Odense, Denmark. pp.289-298, ⟨10.1007/978-3-642-33093-3_29⟩. ⟨hal-00731475⟩
  • Didier Marin, Jérémie Decock, Lionel Rigoux, Olivier Sigaud. Apprentissage de politiques efficaces avec XCSF et CEPS. JFPDA 2011, 2011, Rouen, France. pp.298-310. ⟨hal-00703774⟩
  • Didier Marin, Jérémie Decock, Lionel Rigoux, Olivier Sigaud. Learning Cost-Efficient Control Policies with XCSF: Generalization Capabilities and Further Improvement. GECCO 2011, 2011, Dublin, Ireland. pp.1235-1242. ⟨hal-00703760⟩
  • Guillaume Sicard, Camille Salaün, Serena Ivaldi, Vincent Padois, Olivier Sigaud. Learning the velocity kinematics of iCub for model-based control: XCSF versus LWPR. 11th IEEE-RAS International Conference on Humanoid Robots - Humanoids 2011, Oct 2011, Bled, Slovenia. pp.570--575, ⟨10.1109/Humanoids.2011.6100818⟩. ⟨hal-00624056v2⟩
  • Camille Salaün, Vincent Padois, Olivier Sigaud. Control of redundant robots using learned models: an operational space control approach. IEEE/RSJ International Conference on Intelligent Robots and Systems, Oct 2009, Saint Louis, United States. pp.878--885, ⟨10.1109/IROS.2009.5354438⟩. ⟨hal-00624322⟩
  • Samuel Landau, Olivier Sigaud, Sébastien Picault, Pierre Gérard. An Experimental Comparison between ATNoSFERES and ACS. 6th International Workshop on Learning Classifier Systems (IWLCS'2003), 2003, Chicago, United States. pp.144-160. ⟨hal-00860490⟩
  • Samuel Landau, Sébastien Picault, Olivier Sigaud, Pierre Gérard. Further Comparison between ATNoSFERES and XCSM. IWLCS 2002 - 5th International Workshop on Learning Classifier Systems, Sep 2002, Granada, Spain. pp.99-117, ⟨10.1007/978-3-540-40029-5_7⟩. ⟨hal-00860450⟩
  • Samuel Landau, Sébastien Picault, Olivier Sigaud, Pierre Gérard. A Comparison between ATNoSFERES and XCSM. GECCO 2002: Genetic and Evolutionary Computation Conference, Jul 2002, New York, United States. pp.926-933. ⟨hal-00860423⟩

Books2 documents

  • Olivier Sigaud, Olivier Buffet. Processus décisionnels de Markov en intelligence artificielle. Lavoisier - Hermes Science Publications, 1 - principes généraux et applications, pp.258, 2008, IC2 - informatique et systèmes d'information, Bernard Dubuisson - Jean-Charles Pomerol, 978-2746220577. ⟨inria-00326864⟩
  • Olivier Buffet, Olivier Sigaud. Processus décisionnels de Markov en intelligence artificielle. Lavoisier - Hermes Science Publications, 2 - méthodes avancées et applications, pp.256, 2008, IC2 - informatique et systèmes d'information, Bernard Dubuisson - Jean-Charles Pomerol, 978-2746220584. ⟨inria-00326860⟩

Book sections3 documents

  • Isabelle Bloch, Régis Clouard, Marinette Revenu, Olivier Sigaud. Intelligence artificielle et reconnaissance des formes, vision, apprentissage pour la robotique. L'Intelligence Artificielle : Frontières et Applications, Volume 3, série : Panorama de l'Intelligence Artificielle, Editions CEPADUES, 30 pp, 2014, 9782364930438. ⟨hal-00995039⟩
  • Camille Salaün, Vincent Padois, Olivier Sigaud. Learning Forward Models for the Operational Space Control of Redundant Robots. Olivier Sigaud and Jan Peters. From Motor Learning to Interaction Learning in Robots, Springer, pp.169--192, 2010, Studies in Computational Intelligence, volume 264, ⟨10.1007/978-3-642-05181-4_8⟩. ⟨hal-00586453⟩
  • Camille Salaün, Vincent Padois, Olivier Sigaud. A Two-Level Model of Anticipation-Based Motor Learning for Whole Body Motion. Giovanni Pezzulo, Martin V. Butz, Olivier Sigaud and Gianluca Baldassarre. Anticipatory Behavior in Adaptive Learning Systems: From Psychological Theories to Artificial Cognitive System, Springer, pp.229--246, 2009, Lecture Notes in Computer Science Volume 5499, ⟨10.1007/978-3-642-02565-5_13⟩. ⟨hal-00624103⟩

Preprints, Working Papers, ...6 documents

  • Cédric Colas, Tristan Karch, Olivier Sigaud, Pierre-Yves Oudeyer. Intrinsically Motivated Goal-Conditioned Reinforcement Learning: a Short Survey. 2021. ⟨hal-03099891⟩
  • 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⟩
  • Stephane Doncieux, Nicolas Bredeche, Léni Le Goff, Benoît Girard, Alexandre Coninx, et al.. DREAM Architecture: a Developmental Approach to Open-Ended Learning in Robotics. 2020. ⟨hal-02562103⟩
  • Thomas Pierrot, Nicolas Perrin, Feryal Behbahani, Alexandre Laterre, Olivier Sigaud, et al.. Learning Compositional Neural Programs for Continuous Control. 2020. ⟨hal-03083161⟩
  • Geoffrey Cideron, Thomas Pierrot, Nicolas Perrin, Karim Beguir, Olivier Sigaud. QD-RL: Efficient Mixing of Quality and Diversity in Reinforcement Learning. 2020. ⟨hal-03083159⟩
  • Freek Stulp, Olivier Sigaud. Policy Improvement Methods: Between Black-Box Optimization and Episodic Reinforcement Learning. 2012. ⟨hal-00738463⟩