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2020 – today
- 2024
[c67]Théo Cachet, Christopher R. Dance, Olivier Sigaud:
Bridging Environments and Language with Rendering Functions and Vision-Language Models. ICML 2024- [i50]Alexandre Chenu, Olivier Serris, Olivier Sigaud, Nicolas Perrin-Gilbert:
Single-Reset Divide & Conquer Imitation Learning. CoRR abs/2402.09355 (2024) - [i49]Zakariae El Asri, Olivier Sigaud, Nicolas Thome:
Physics-Informed Model and Hybrid Planning for Efficient Dyna-Style Reinforcement Learning. CoRR abs/2407.02217 (2024) - 2023
- [j33]Olivier Sigaud
, Ahmed Akakzia, Hugo Caselles-Dupré, Cédric Colas, Pierre-Yves Oudeyer, Mohamed Chetouani:
Toward Teachable Autotelic Agents. IEEE Trans. Cogn. Dev. Syst. 15(3): 1070-1084 (2023) - [j32]Olivier Sigaud:
Combining Evolution and Deep Reinforcement Learning for Policy Search: A Survey. ACM Trans. Evol. Learn. Optim. 3(3): 10:1-10:20 (2023) - [c66]Thomas Carta, Clément Romac, Thomas Wolf, Sylvain Lamprier, Olivier Sigaud, Pierre-Yves Oudeyer:
Grounding Large Language Models in Interactive Environments with Online Reinforcement Learning. ICML 2023: 3676-3713 - [c65]Nicolas Castanet, Olivier Sigaud, Sylvain Lamprier:
Stein Variational Goal Generation for adaptive Exploration in Multi-Goal Reinforcement Learning. ICML 2023: 3714-3731 - [c64]Vaynee Sungeelee, Antoine Loriette, Olivier Sigaud, Baptiste Caramiaux:
Human-Machine Co-Learning : Case Study on Motor Skill Acquisition. IHM 2023: 16:1-16:13 - [i48]Thomas Carta, Clément Romac, Thomas Wolf, Sylvain Lamprier, Olivier Sigaud, Pierre-Yves Oudeyer:
Grounding Large Language Models in Interactive Environments with Online Reinforcement Learning. CoRR abs/2302.02662 (2023) - [i47]Hugo Caselles-Dupré, Olivier Sigaud, Mohamed Chetouani:
Enhancing Agent Communication and Learning through Action and Language. CoRR abs/2308.10842 (2023) - [i46]Clémence Grislain, Hugo Caselles-Dupré, Olivier Sigaud, Mohamed Chetouani:
Utility-based Adaptive Teaching Strategies using Bayesian Theory of Mind. CoRR abs/2309.17275 (2023) - [i45]Antonin Raffin, Olivier Sigaud, Jens Kober, Alin Albu-Schäffer, João Silvério, Freek Stulp:
A Simple Open-Loop Baseline for Reinforcement Learning Locomotion Tasks. CoRR abs/2310.05808 (2023) - [i44]Olivier Sigaud, Gianluca Baldassarre, Cédric Colas, Stéphane Doncieux, Richard J. Duro, Nicolas Perrin-Gilbert, Vieri Giuliano Santucci:
A Definition of Open-Ended Learning Problems for Goal-Conditioned Agents. CoRR abs/2311.00344 (2023) - 2022
- [j31]Aloïs Pourchot, Kévin Bailly, Alexis Ducarouge, Olivier Sigaud:
An extensive appraisal of weight-sharing on the NAS-Bench-101 benchmark. Neurocomputing 498: 28-42 (2022) - [j30]Cédric Colas, Tristan Karch, Olivier Sigaud, Pierre-Yves Oudeyer:
Autotelic Agents with Intrinsically Motivated Goal-Conditioned Reinforcement Learning: A Short Survey. J. Artif. Intell. Res. 74: 1159-1199 (2022) - [c63]Ahmed Akakzia, Olivier Sigaud:
Learning Object-Centered Autotelic Behaviors with Graph Neural Networks. CoLLAs 2022: 351-365 - [c62]Thomas Pierrot, Valentin Macé, Félix Chalumeau, Arthur Flajolet, Geoffrey Cideron, Karim Beguir, Antoine Cully, Olivier Sigaud, Nicolas Perrin-Gilbert:
Diversity policy gradient for sample efficient quality-diversity optimization. GECCO 2022: 1075-1083 - [c61]Aloïs Pourchot, Kévin Bailly, Alexis Ducarouge, Olivier Sigaud:
Neural Architecture Search for Fracture Classification. ICIP 2022: 3226-3230 - [c60]Alexandre Chenu, Nicolas Perrin-Gilbert, Olivier Sigaud:
Divide & Conquer Imitation Learning. IROS 2022: 8630-8637 - [c59]Thomas Carta, Pierre-Yves Oudeyer, Olivier Sigaud, Sylvain Lamprier:
EAGER: Asking and Answering Questions for Automatic Reward Shaping in Language-guided RL. NeurIPS 2022 - [c58]Hugo Caselles-Dupré, Olivier Sigaud, Mohamed Chetouani:
Pragmatically Learning from Pedagogical Demonstrations in Multi-Goal Environments. NeurIPS 2022 - [i43]Ahmed Akakzia, Olivier Serris, Olivier Sigaud, Cédric Colas:
Help Me Explore: Minimal Social Interventions for Graph-Based Autotelic Agents. CoRR abs/2202.05129 (2022) - [i42]Hugo Caselles-Dupré, Mohamed Chetouani, Olivier Sigaud:
Pedagogical Demonstrations and Pragmatic Learning in Artificial Tutor-Learner Interactions. CoRR abs/2203.00111 (2022) - [i41]Olivier Sigaud:
Combining Evolution and Deep Reinforcement Learning for Policy Search: a Survey. CoRR abs/2203.14009 (2022) - [i40]Ahmed Akakzia, Olivier Sigaud:
Learning Object-Centered Autotelic Behaviors with Graph Neural Networks. CoRR abs/2204.05141 (2022) - [i39]Alexandre Chenu, Nicolas Perrin-Gilbert, Olivier Sigaud:
Divide & Conquer Imitation Learning. CoRR abs/2204.07404 (2022) - [i38]Hugo Caselles-Dupré, Olivier Sigaud, Mohamed Chetouani:
Pragmatically Learning from Pedagogical Demonstrations in Multi-Goal Environments. CoRR abs/2206.04546 (2022) - [i37]Nicolas Castanet, Sylvain Lamprier, Olivier Sigaud:
Stein Variational Goal Generation For Reinforcement Learning in Hard Exploration Problems. CoRR abs/2206.06719 (2022) - [i36]Thomas Carta, Sylvain Lamprier, Pierre-Yves Oudeyer, Olivier Sigaud:
EAGER: Asking and Answering Questions for Automatic Reward Shaping in Language-guided RL. CoRR abs/2206.09674 (2022) - [i35]Maël Franceschetti, Coline Lacoux, Ryan Ohouens, Antonin Raffin, Olivier Sigaud:
Making Reinforcement Learning Work on Swimmer. CoRR abs/2208.07587 (2022) - [i34]Hugo Caselles-Dupré, Olivier Sigaud, Mohamed Chetouani:
Overcoming Referential Ambiguity in Language-Guided Goal-Conditioned Reinforcement Learning. CoRR abs/2209.12758 (2022) - [i33]Alexandre Chenu, Olivier Serris, Olivier Sigaud, Nicolas Perrin-Gilbert:
Leveraging Sequentiality in Reinforcement Learning from a Single Demonstration. CoRR abs/2211.04786 (2022) - 2021
- [j29]Pierre Fournier, Cédric Colas, Mohamed Chetouani, Olivier Sigaud:
CLIC: Curriculum Learning and Imitation for Object Control in Nonrewarding Environments. IEEE Trans. Cogn. Dev. Syst. 13(2): 239-248 (2021) - [c57]Anis Najar, Olivier Sigaud, Mohamed Chetouani:
Teaching a Robot with Unlabeled Instructions: The TICS Architecture. AAMAS 2021: 1738-1739 - [c56]Thomas Pierrot, Nicolas Perrin-Gilbert, Olivier Sigaud:
First-Order and Second-Order Variants of the Gradient Descent in a Unified Framework. ICANN (2) 2021: 197-208 - [c55]Alexandre Chenu, Nicolas Perrin, Stéphane Doncieux, Olivier Sigaud:
Selection-Expansion: A Unifying Framework for Motion-Planning and Diversity Search Algorithms. ICANN (4) 2021: 568-579 - [c54]Ahmed Akakzia, Cédric Colas, Pierre-Yves Oudeyer, Mohamed Chetouani, Olivier Sigaud:
Grounding Language to Autonomously-Acquired Skills via Goal Generation. ICLR 2021 - [i32]Alexandre Chenu, Nicolas Perrin-Gilbert, Stéphane Doncieux, Olivier Sigaud:
Selection-Expansion: A Unifying Framework for Motion-Planning and Diversity Search Algorithms. CoRR abs/2104.04768 (2021) - [i31]Olivier Sigaud, Hugo Caselles-Dupré, Cédric Colas, Ahmed Akakzia, Pierre-Yves Oudeyer, Mohamed Chetouani:
Towards Teachable Autonomous Agents. CoRR abs/2105.11977 (2021) - 2020
- [j28]Anis Najar, Olivier Sigaud, Mohamed Chetouani:
Interactively shaping robot behaviour with unlabeled human instructions. Auton. Agents Multi Agent Syst. 34(2): 35 (2020) - [j27]Ryan Lober, Olivier Sigaud, Vincent Padois:
Task Feasibility Maximization Using Model-Free Policy Search and Model-Based Whole-Body Control. Frontiers Robotics AI 7: 61 (2020) - [c53]Guillaume Matheron, Nicolas Perrin, Olivier Sigaud:
PBCS: Efficient Exploration and Exploitation Using a Synergy Between Reinforcement Learning and Motion Planning. ICANN (2) 2020: 295-307 - [c52]Guillaume Matheron, Nicolas Perrin, Olivier Sigaud:
Understanding Failures of Deterministic Actor-Critic with Continuous Action Spaces and Sparse Rewards. ICANN (2) 2020: 308-320 - [c51]Félix Rutard, Olivier Sigaud, Mohamed Chetouani:
TIRL: Enriching Actor-Critic RL with non-expert human teachers and a Trust Model. RO-MAN 2020: 604-611 - [p3]Isabelle Bloch, Régis Clouard, Marinette Revenu, Olivier Sigaud:
Artificial Intelligence and Pattern Recognition, Vision, Learning. A Guided Tour of Artificial Intelligence Research (3) (III) 2020: 337-364 - [i30]Aloïs Pourchot, Alexis Ducarouge, Olivier Sigaud:
To Share or Not To Share: A Comprehensive Appraisal of Weight-Sharing. CoRR abs/2002.04289 (2020) - [i29]Guillaume Matheron, Nicolas Perrin, Olivier Sigaud:
PBCS : Efficient Exploration and Exploitation Using a Synergy between Reinforcement Learning and Motion Planning. CoRR abs/2004.11667 (2020) - [i28]Stéphane Doncieux, Nicolas Bredèche, Leni K. Le Goff, Benoît Girard, Alexandre Coninx, Olivier Sigaud, Mehdi Khamassi, Natalia Díaz Rodríguez, David Filliat, Timothy M. Hospedales, A. E. Eiben, Richard J. Duro:
DREAM Architecture: a Developmental Approach to Open-Ended Learning in Robotics. CoRR abs/2005.06223 (2020) - [i27]Cédric Colas, Ahmed Akakzia, Pierre-Yves Oudeyer, Mohamed Chetouani, Olivier Sigaud:
Language-Conditioned Goal Generation: a New Approach to Language Grounding for RL. CoRR abs/2006.07043 (2020) - [i26]Ahmed Akakzia, Cédric Colas, Pierre-Yves Oudeyer, Mohamed Chetouani, Olivier Sigaud:
DECSTR: Learning Goal-Directed Abstract Behaviors using Pre-Verbal Spatial Predicates in Intrinsically Motivated Agents. CoRR abs/2006.07185 (2020) - [i25]Geoffrey Cideron, Thomas Pierrot, Nicolas Perrin, Karim Beguir, Olivier Sigaud:
QD-RL: Efficient Mixing of Quality and Diversity in Reinforcement Learning. CoRR abs/2006.08505 (2020) - [i24]Thomas Pierrot, Nicolas Perrin, Feryal M. P. Behbahani, Alexandre Laterre, Olivier Sigaud, Karim Beguir, Nando de Freitas:
Learning Compositional Neural Programs for Continuous Control. CoRR abs/2007.13363 (2020) - [i23]Louis Monier, Jakub Kmec, Alexandre Laterre, Thomas Pierrot, Valentin Courgeau, Olivier Sigaud, Karim Beguir:
Offline Reinforcement Learning Hands-On. CoRR abs/2011.14379 (2020) - [i22]Cédric Colas, Tristan Karch, Olivier Sigaud, Pierre-Yves Oudeyer:
Intrinsically Motivated Goal-Conditioned Reinforcement Learning: a Short Survey. CoRR abs/2012.09830 (2020)
2010 – 2019
- 2019
- [j26]Olivier Sigaud, Freek Stulp:
Policy search in continuous action domains: An overview. Neural Networks 113: 28-40 (2019) - [c50]Cédric Colas, Olivier Sigaud, Pierre-Yves Oudeyer:
A Hitchhiker's Guide to Statistical Comparisons of Reinforcement Learning Algorithms. RML@ICLR 2019 - [c49]Aloïs Pourchot, Olivier Sigaud:
CEM-RL: Combining evolutionary and gradient-based methods for policy search. ICLR (Poster) 2019 - [c48]Cédric Colas, Pierre-Yves Oudeyer, Olivier Sigaud, Pierre Fournier, Mohamed Chetouani:
CURIOUS: Intrinsically Motivated Modular Multi-Goal Reinforcement Learning. ICML 2019: 1331-1340 - [c47]Thomas Pierrot, Guillaume Ligner, Scott E. Reed, Olivier Sigaud, Nicolas Perrin, Alexandre Laterre, David Kas, Karim Beguir, Nando de Freitas:
Learning Compositional Neural Programs with Recursive Tree Search and Planning. NeurIPS 2019: 14646-14656 - [i21]Pierre Fournier, Olivier Sigaud, Cédric Colas, Mohamed Chetouani:
CLIC: Curriculum Learning and Imitation for feature Control in non-rewarding environments. CoRR abs/1901.09720 (2019) - [i20]Anis Najar, Olivier Sigaud, Mohamed Chetouani:
Interactively shaping robot behaviour with unlabeled human instructions. CoRR abs/1902.01670 (2019) - [i19]Chenyang Zhao, Olivier Sigaud, Freek Stulp, Timothy M. Hospedales:
Investigating Generalisation in Continuous Deep Reinforcement Learning. CoRR abs/1902.07015 (2019) - [i18]Cédric Colas, Olivier Sigaud, Pierre-Yves Oudeyer:
A Hitchhiker's Guide to Statistical Comparisons of Reinforcement Learning Algorithms. CoRR abs/1904.06979 (2019) - [i17]Thomas Pierrot, Guillaume Ligner, Scott E. Reed, Olivier Sigaud, Nicolas Perrin, Alexandre Laterre, David Kas, Karim Beguir, Nando de Freitas:
Learning Compositional Neural Programs with Recursive Tree Search and Planning. CoRR abs/1905.12941 (2019) - [i16]Guillaume Matheron, Nicolas Perrin, Olivier Sigaud:
The problem with DDPG: understanding failures in deterministic environments with sparse rewards. CoRR abs/1911.11679 (2019) - 2018
- [j25]Stéphane Doncieux, David Filliat, Natalia Díaz Rodríguez, Timothy M. Hospedales, Richard J. Duro, Alexandre Coninx, Diederik M. Roijers, Benoît Girard, Nicolas Perrin, Olivier Sigaud:
Open-Ended Learning: A Conceptual Framework Based on Representational Redescription. Frontiers Neurorobotics 12: 59 (2018) - [j24]Nicolas Le Hir, Olivier Sigaud, Alban Laflaquière:
Identification of Invariant Sensorimotor Structures as a Prerequisite for the Discovery of Objects. Frontiers Robotics AI 5: 70 (2018) - [j23]Francesco Romano, Gabriele Nava, Morteza Azad, Jernej Camernik, Stefano Dafarra, Oriane Dermy, Claudia Latella, Maria Lazzaroni, Ryan Lober, Marta Lorenzini, Daniele Pucci, Olivier Sigaud, Silvio Traversaro, Jan Babic, Serena Ivaldi, Michael N. Mistry, Vincent Padois, Francesco Nori:
The CoDyCo Project Achievements and Beyond: Toward Human Aware Whole-Body Controllers for Physical Human Robot Interaction. IEEE Robotics Autom. Lett. 3(1): 516-523 (2018) - [c46]Alexandre Péré, Sébastien Forestier, Olivier Sigaud, Pierre-Yves Oudeyer:
Unsupervised Learning of Goal Spaces for Intrinsically Motivated Goal Exploration. ICLR (Poster) 2018 - [c45]Cédric Colas, Olivier Sigaud, Pierre-Yves Oudeyer:
GEP-PG: Decoupling Exploration and Exploitation in Deep Reinforcement Learning Algorithms. ICML 2018: 1038-1047 - [c44]Cédric Colas, Olivier Sigaud, Pierre-Yves Oudeyer:
GEP-PG: Decoupling Exploration and Exploitation in Deep Reinforcement Learning Algorithms. JFPDA 2018 - [i15]Cédric Colas, Olivier Sigaud, Pierre-Yves Oudeyer:
GEP-PG: Decoupling Exploration and Exploitation in Deep Reinforcement Learning Algorithms. CoRR abs/1802.05054 (2018) - [i14]Alexandre Péré, Sébastien Forestier, Olivier Sigaud, Pierre-Yves Oudeyer:
Unsupervised Learning of Goal Spaces for Intrinsically Motivated Goal Exploration. CoRR abs/1803.00781 (2018) - [i13]Olivier Sigaud, Freek Stulp:
Policy Search in Continuous Action Domains: an Overview. CoRR abs/1803.04706 (2018) - [i12]Cédric Colas, Olivier Sigaud, Pierre-Yves Oudeyer:
How Many Random Seeds? Statistical Power Analysis in Deep Reinforcement Learning Experiments. CoRR abs/1806.08295 (2018) - [i11]Pierre Fournier, Olivier Sigaud, Mohamed Chetouani, Pierre-Yves Oudeyer:
Accuracy-based Curriculum Learning in Deep Reinforcement Learning. CoRR abs/1806.09614 (2018) - [i10]Aloïs Pourchot, Nicolas Perrin, Olivier Sigaud:
Importance mixing: Improving sample reuse in evolutionary policy search methods. CoRR abs/1808.05832 (2018) - [i9]Aloïs Pourchot, Olivier Sigaud:
CEM-RL: Combining evolutionary and gradient-based methods for policy search. CoRR abs/1810.01222 (2018) - [i8]Nicolas Le Hir, Olivier Sigaud, Alban Laflaquière:
Identification of Invariant Sensorimotor Structures as a Prerequisite for the Discovery of Objects. CoRR abs/1810.05057 (2018) - [i7]Cédric Colas, Pierre Fournier, Olivier Sigaud, Pierre-Yves Oudeyer:
CURIOUS: Intrinsically Motivated Multi-Task, Multi-Goal Reinforcement Learning. CoRR abs/1810.06284 (2018) - [i6]Thomas Pierrot, Nicolas Perrin, Olivier Sigaud:
First-order and second-order variants of the gradient descent: a unified framework. CoRR abs/1810.08102 (2018) - 2017
- [c43]Chenyang Zhao, Timothy M. Hospedales, Freek Stulp, Olivier Sigaud:
Tensor Based Knowledge Transfer Across Skill Categories for Robot Control. IJCAI 2017: 3462-3468 - 2016
- [j22]Olivier Sigaud, Alain Droniou:
Towards Deep Developmental Learning. IEEE Trans. Cogn. Dev. Syst. 8(2): 99-114 (2016) - [c42]Ryan Lober, Vincent Padois, Olivier Sigaud:
Efficient reinforcement learning for humanoid whole-body control. Humanoids 2016: 684-689 - [c41]Anis Najar, Olivier Sigaud, Mohamed Chetouani:
Training a robot with evaluative feedback and unlabeled guidance signals. RO-MAN 2016: 261-266 - [i5]Arnaud de Froissard de Broissia, Olivier Sigaud:
Actor-critic versus direct policy search: a comparison based on sample complexity. CoRR abs/1606.09152 (2016) - 2015
- [j21]Freek Stulp, Olivier Sigaud:
Many regression algorithms, one unified model: A review. Neural Networks 69: 60-79 (2015) - [j20]Alain Droniou, Serena Ivaldi, Olivier Sigaud:
Deep unsupervised network for multimodal perception, representation and classification. Robotics Auton. Syst. 71: 83-98 (2015) - [c40]Anis Najar, Olivier Sigaud, Mohamed Chetouani:
Socially Guided XCS: Using Teaching Signals to Boost Learning. GECCO (Companion) 2015: 1021-1028 - [c39]Ryan Lober, Vincent Padois, Olivier Sigaud:
Variance modulated task prioritization in Whole-Body Control. IROS 2015: 3944-3949 - [c38]Anis Najar, Olivier Sigaud, Mohamed Chetouani:
Social-Task Learning for HRI. ICSR 2015: 472-481 - [i4]Olivier Sigaud, Clément Masson, David Filliat, Freek Stulp:
Gated networks: an inventory. CoRR abs/1512.03201 (2015) - 2014
- [j19]Serena Ivaldi, Salvatore Maria Anzalone, Woody Rousseau, Olivier Sigaud, Mohamed Chetouani:
Robot initiative in a team learning task increases the rhythm of interaction but not the perceived engagement. Frontiers Neurorobotics 8: 5 (2014) - [j18]Florian Lesaint, Olivier Sigaud, Shelly B. Flagel, Terry E. Robinson, Mehdi Khamassi:
Modelling Individual Differences in the Form of Pavlovian Conditioned Approach Responses: A Dual Learning Systems Approach with Factored Representations. PLoS Comput. Biol. 10(2) (2014) - [j17]Serena Ivaldi, Sao Mai Nguyen, Natalia Lyubova, Alain Droniou, Vincent Padois, David Filliat, Pierre-Yves Oudeyer, Olivier Sigaud:
Object Learning Through Active Exploration. IEEE Trans. Auton. Ment. Dev. 6(1): 56-72 (2014) - [c37]Ryan Lober, Vincent Padois, Olivier Sigaud:
Multiple task optimization using dynamical movement primitives for whole-body reactive control. Humanoids 2014: 193-198 - [c36]Alain Droniou, Serena Ivaldi, Olivier Sigaud:
Learning a repertoire of actions with deep neural networks. ICDL-EPIROB 2014: 229-234 - 2013
- [j16]Freek Stulp, Olivier Sigaud:
Robot Skill Learning: From Reinforcement Learning to Evolution Strategies. Paladyn J. Behav. Robotics 4(1): 49-61 (2013) - [j15]Didier Marin, Lionel Rigoux, Olivier Sigaud:
Apprentissage et optimisation de politiques pour un bras articulé actionné par des muscles. Rev. d'Intelligence Artif. 27(2): 195-215 (2013) - [j14]Olivier Sigaud, Freek Stulp:
Adaptation de la matrice de covariance pour l'apprentissage par renforcement direct. Rev. d'Intelligence Artif. 27(2): 243-263 (2013) - [c35]Sao Mai Nguyen, Serena Ivaldi, Natalia Lyubova, Alain Droniou, Damien Gérardeaux-Viret, David Filliat, Vincent Padois, Olivier Sigaud, Pierre-Yves Oudeyer:
Learning to recognize objects through curiosity-driven manipulation with the iCub humanoid robot. ICDL-EPIROB 2013: 1-8 - [c34]Alain Droniou, Olivier Sigaud:
Gated Autoencoders with Tied Input Weights. ICML (2) 2013: 154-162 - 2012
- [j13]Patrick O. Stalph, Jérémie Rubinsztajn, Olivier Sigaud, Martin V. Butz:
Function approximation with LWPR and XCSF: a comparative study. Evol. Intell. 5(2): 103-116 (2012) - [j12]Martin V. Butz, Olivier Sigaud:
XCSF with local deletion: preventing detrimental forgetting. Evol. Intell. 5(2): 117-127 (2012) - [j11]Serena Ivaldi, Olivier Sigaud, Bastien Berret, Francesco Nori:
From humans to humanoids: The optimal control framework. Paladyn J. Behav. Robotics 3(2): 75-91 (2012) - [c33]Salvatore Maria Anzalone, Serena Ivaldi, Olivier Sigaud, Mohamed Chetouani:
Multimodal People Engagement with iCub. BICA 2012: 59-64 - [c32]Serena Ivaldi, Natalia Lyubova, Damien Gérardeaux-Viret, Alain Droniou, Salvatore Maria Anzalone, Mohamed Chetouani, David Filliat, Olivier Sigaud:
Perception and human interaction for developmental learning of objects and affordances. Humanoids 2012: 248-254 - [c31]Freek Stulp, Olivier Sigaud:
Path Integral Policy Improvement with Covariance Matrix Adaptation. ICML 2012 - [c30]Alain Droniou, Serena Ivaldi, Vincent Padois, Olivier Sigaud:
Autonomous online learning of velocity kinematics on the iCub: A comparative study. IROS 2012: 3577-3582 - [c29]Jean Bellot, Olivier Sigaud, Mehdi Khamassi:
Which Temporal Difference Learning Algorithm Best Reproduces Dopamine Activity in a Multi-choice Task? SAB 2012: 289-298 - [i3]Freek Stulp, Olivier Sigaud:
Path Integral Policy Improvement with Covariance Matrix Adaptation. CoRR abs/1206.4621 (2012) - [i2]Thomas Degris, Olivier Sigaud, Pierre-Henri Wuillemin:
Chi-square Tests Driven Method for Learning the Structure of Factored MDPs. CoRR abs/1206.6842 (2012) - 2011
- [j10]Olivier Sigaud, Camille Salaün, Vincent Padois:
On-line regression algorithms for learning mechanical models of robots: A survey. Robotics Auton. Syst. 59(12): 1115-1129 (2011) - [c28]Martin V. Butz, Olivier Sigaud:
XCSF with local deletion: preventing detrimental forgetting. GECCO (Companion) 2011: 383-390 - [c27]Didier Marin, Jérémie Decock, Lionel Rigoux, Olivier Sigaud:
Learning cost-efficient control policies with XCSF: generalization capabilities and further improvement. GECCO 2011: 1235-1242 - [c26]Guillaume Sicard, Camille Salaün, Serena Ivaldi, Vincent Padois, Olivier Sigaud:
Learning the velocity kinematics of ICUB for model-based control: XCSF versus LWPR. Humanoids 2011: 570-575 - 2010
- [c25]