[1] Stephane Doncieux. Apprendre aux robots à faire face à l'imprévu. Industries et Technologies, 1045, 2021. Cahier Technique. [ bib ]
[2] Antonin Raffin, Bastian Deutschmann, and Freek Stulp. Fault-tolerant six-dof pose estimation for tendon-driven continuum mechanisms. Frontiers in Robotics and AI, 8:11, 2021. [ bib | https ]
[3] Achkan Salehi, Alexandre Coninx, and Stephane Doncieux. BR-NS: An Archive-Less Approach to Novelty Search, page 172–179. Association for Computing Machinery, New York, NY, USA, 2021. [ bib | https ]
[4] Antonin Raffin, Jens Kober, and Freek Stulp. Smooth exploration for robotic reinforcement learning. In Conference on Robot Learning, 2021. [ bib ]
[5] Antonin Raffin, Ashley Hill, Adam Gleave, Anssi Kanervisto, Maximilian Ernestus, and Noah Dormann. Stable-baselines3: Reliable reinforcement learning implementations. Journal of Machine Learning Research, 22(268):1--8, 2021. [ bib | .html ]
[6] Astrid Merckling, Nicolas Perrin-Gilbert, Alex Coninx, and Stéphane Doncieux. Exploratory state representation learning. Frontiers in Robotics and AI, 9, 2022. [ bib ]
[7] Salehi Achkan, Achkan Salehi, Alexandre Coninx, and Stephane Doncieux. Few-shot quality-diversity optimization. IEEE Robotics and Automation Letters, pages 1--10, 2022. [ bib ]

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