Bibliography

Major publications by the team in recent years

• 1A. Baranes, P.-Y. Oudeyer.
  
  RIAC: Robust Intrinsically Motivated Exploration and Active Learning, in: IEEE Trans. on Auto. Ment. Dev., 2009, vol. 1, n^o 3, pp. 155-169.
  
  http://www.pyoudeyer.com/TAMDBaranesOudeyer09.pdf
• 2A. Baranes, P.-Y. Oudeyer.
  
  The Interaction of Maturational Constraints and Intrinsic Motivations in Active Motor Development, in: ICDL - EpiRob, Frankfurt, Germany, August 2011.
  
  http://hal.inria.fr/hal-00646585/en
• 3A. Baranes, P.-Y. Oudeyer.
  
  Active Learning of Inverse Models with Intrinsically Motivated Goal Exploration in Robots, in: Robotics and Autonomous Systems, January 2013, vol. 61, n^o 1, pp. 69-73. [ DOI : 10.1016/j.robot.2012.05.008 ]
  
  https://hal.inria.fr/hal-00788440
• 4A. Baranes, P.-Y. Oudeyer, J. Gottlieb.
  
  The effects of task difficulty, novelty and the size of the search space on intrinsically motivated exploration, in: Frontiers in Neuroscience, October 2014, vol. 8, n^o 317, pp. 1-9. [ DOI : 10.3389/fnins.2014.00317 ]
  
  https://hal.inria.fr/hal-01087227
• 5A. Baranes, P.-Y. Oudeyer, J. Gottlieb.
  
  Eye movements reveal epistemic curiosity in human observers, in: Vision Research, November 2015, vol. 117, 9 p. [ DOI : 10.1016/j.visres.2015.10.009 ]
  
  https://hal.inria.fr/hal-01250727
• 6A. Baranes, P.-Y. Oudeyer.
  
  R-IAC: Robust Intrinsically Motivated Exploration and Active Learning, in: IEEE Transaction on Autonomous Mental Development, 12 2009.
• 7A. Baranès, P. Oudeyer.
  
  R-IAC: Robust intrinsically motivated exploration and active learning, in: Autonomous Mental Development, IEEE Transactions on, 2009, vol. 1, n^o 3, pp. 155–169.
• 8F. Benureau, P.-Y. Oudeyer.
  
  Behavioral Diversity Generation in Autonomous Exploration through Reuse of Past Experience, in: Frontiers in Robotics and AI, March 2016, vol. 3, n^o 8. [ DOI : 10.3389/frobt.2016.00008 ]
  
  https://hal.inria.fr/hal-01404329
• 9J. Buchli, F. Stulp, E. Theodorou, S. Schaal.
  
  Learning Variable Impedance Control, in: International Journal of Robotics Research, 2011, vol. 30, n^o 7, pp. 820-833.
  
  http://ijr.sagepub.com/content/early/2011/03/31/0278364911402527
• 10L.-C. Caron, Y. Song, D. Filliat, A. Gepperth.
  
  Neural network based 2D/3D fusion for robotic object recognition, in: ESANN, Bruges, Belgium, May 2014, pp. 127 - 132.
  
  https://hal.archives-ouvertes.fr/hal-01012090
• 11T. Cederborg, P.-Y. Oudeyer.
  
  From Language to Motor Gavagai: Unified Imitation Learning of Multiple Linguistic and Non-linguistic Sensorimotor Skills, in: IEEE Transactions on Autonomous Mental Development (TAMD), 2013.
  
  https://hal.inria.fr/hal-00910982
• 12Y. Chen, J.-B. Bordes, D. Filliat.
  
  An experimental comparison between NMF and LDA for active cross-situational object-word learning, in: ICDL EPIROB 2016, Cergy-Pontoise, France, Proceedings of the The Sixth Joint IEEE International Conference Developmental Learning and Epigenetic Robotics (ICDL EPIROB 2016), September 2016.
  
  https://hal.archives-ouvertes.fr/hal-01370853
• 13Y. Chen, D. Filliat.
  
  Cross-situational noun and adjective learning in an interactive scenario, in: ICDL-Epirob, Providence, United States, August 2015.
  
  https://hal.archives-ouvertes.fr/hal-01170674
• 14B. Clement, D. Roy, P.-Y. Oudeyer, M. Lopes.
  
  Multi-Armed Bandits for Intelligent Tutoring Systems, in: Journal of Educational Data Mining (JEDM), June 2015, vol. 7, n^o 2, pp. 20–48.
  
  https://hal.inria.fr/hal-00913669
• 15C. Craye, D. Filliat, J.-F. Goudou.
  
  Environment Exploration for Object-Based Visual Saliency Learning, in: ICRA 2016, Stockholm, Sweden, Proceedings of the International Conference on Robotics and Automation, May 2016.
  
  https://hal.archives-ouvertes.fr/hal-01289159
• 16C. Craye, D. Filliat, J.-F. Goudou.
  
  RL-IAC: An Exploration Policy for Online Saliency Learning on an Autonomous Mobile Robot, in: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Daejeon, South Korea, October 2016.
  
  https://hal.archives-ouvertes.fr/hal-01392947
• 17T. Degris, M. White, R. Sutton.
  
  Off-Policy Actor-Critic, in: International Conference on Machine Learning, 2012.
  
  http://hal.inria.fr/hal-00764021
• 18S. Forestier, P.-Y. Oudeyer.
  
  Curiosity-Driven Development of Tool Use Precursors: a Computational Model, in: 38th Annual Conference of the Cognitive Science Society (CogSci 2016), Philadelphie, PA, United States, A. Papafragou, D. Grodner, D. Mirman, J. Trueswell (editors), Proceedings of the 38th Annual Conference of the Cognitive Science Society, August 2016, pp. 1859–1864.
  
  https://hal.archives-ouvertes.fr/hal-01354013
• 19S. Forestier, P.-Y. Oudeyer.
  
  Modular Active Curiosity-Driven Discovery of Tool Use, in: IEEE/RSJ International Conference on Intelligent Robots and Systems, Daejeon, South Korea, Proceedings of the 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2016.
  
  https://hal.archives-ouvertes.fr/hal-01384566
• 20A. Gepperth.
  
  Efficient online bootstrapping of sensory representations, in: Neural Networks, December 2012. [ DOI : 10.1016/j.neunet.2012.11.002 ]
  
  http://hal.inria.fr/hal-00763660
• 21A. Gepperth, S. Rebhan, S. Hasler, J. Fritsch.
  
  Biased competition in visual processing hierarchies: a learning approach using multiple cues, in: Cognitive Computation, March 2011, vol. 3, n^o 1.
  
  http://hal.archives-ouvertes.fr/hal-00647809/en/
• 22J. Gottlieb, P.-Y. Oudeyer, M. Lopes, A. Baranes.
  
  Information-seeking, curiosity, and attention: computational and neural mechanisms, in: Trends in Cognitive Sciences, November 2013, vol. 17, n^o 11, pp. 585-93. [ DOI : 10.1016/j.tics.2013.09.001 ]
  
  https://hal.inria.fr/hal-00913646
• 23J. Grizou, I. Iturrate, L. Montesano, P.-Y. Oudeyer, M. Lopes.
  
  Calibration-Free BCI Based Control, in: Twenty-Eighth AAAI Conference on Artificial Intelligence, Quebec, Canada, July 2014, pp. 1-8.
  
  https://hal.archives-ouvertes.fr/hal-00984068
• 24T. Guitard, D. Roy, P.-Y. Oudeyer, M. Chevalier.
  
  IniRobot, January 2016, Des activités robotiques pour l'initiation aux sciences du numérique.
  
  https://hal.inria.fr/hal-01412928
• 25I. Iturrate, J. Grizou, O. Jason, P.-Y. Oudeyer, M. Lopes, L. Montesano.
  
  Exploiting Task Constraints for Self-Calibrated Brain-Machine Interface Control Using Error-Related Potentials, in: PLoS ONE, July 2015. [ DOI : 10.1371/journal.pone.0131491 ]
  
  https://hal.inria.fr/hal-01246436
• 26S. Ivaldi, S. M. Nguyen, N. Lyubova, A. Droniou, V. Padois, D. Filliat, P.-Y. Oudeyer, O. Sigaud.
  
  Object learning through active exploration, in: IEEE Transactions on Autonomous Mental Development, 2013, pp. 1-18. [ DOI : 10.1109/TAMD.2013.2280614 ]
  
  https://hal.archives-ouvertes.fr/hal-00919694
• 27F. Kaplan, P.-Y. Oudeyer, B. Bergen.
  
  Computational models in the debate over language learnability, in: Infant and Child Development, 2008, vol. 17, n^o 1, pp. 55–80.
• 28M. Lapeyre.
  
  Poppy: open-source, 3D printed and fully-modular robotic platform for science, art and education, Université de Bordeaux, November 2014.
  
  https://hal.inria.fr/tel-01104641
• 29M. Lapeyre, S. N'Guyen, A. Le Falher, P.-Y. Oudeyer.
  
  Rapid morphological exploration with the Poppy humanoid platform, in: 2014 IEEE-RAS International Conference on Humanoid Robots, Madrid, Spain, November 2014, 8 p.
  
  https://hal.inria.fr/hal-01096344
• 30M. Lapeyre, P. Rouanet, J. Grizou, S. Nguyen, F. Depraetre, A. Le Falher, P.-Y. Oudeyer.
  
  Poppy Project: Open-Source Fabrication of 3D Printed Humanoid Robot for Science, Education and Art, in: Digital Intelligence 2014, Nantes, France, September 2014, 6 p.
  
  https://hal.inria.fr/hal-01096338
• 31M. Lopes, T. Lang, M. Toussaint, P.-Y. Oudeyer.
  
  Exploration in Model-based Reinforcement Learning by Empirically Estimating Learning Progress, in: Neural Information Processing Systems (NIPS), Lake Tahoe, United States, December 2012.
  
  http://hal.inria.fr/hal-00755248
• 32M. Lopes, L. Montesano.
  
  Active Learning for Autonomous Intelligent Agents: Exploration, Curiosity, and Interaction, in: CoRR, 2014, vol. abs/1403.1, 40 p.
• 33M. Lopes, P.-Y. Oudeyer.
  
  The Strategic Student Approach for Life-Long Exploration and Learning, in: IEEE Conference on Development and Learning / EpiRob 2012, San Diego, United States, November 2012.
  
  https://hal.inria.fr/hal-00755216
• 34N. Lyubova, D. Filliat.
  
  Developmental Approach for Interactive Object Discovery, in: Neural Networks (IJCNN), The 2012 International Joint Conference on, Australia, June 2012, pp. 1-7. [ DOI : 10.1109/IJCNN.2012.6252606 ]
  
  https://hal.archives-ouvertes.fr/hal-00755298
• 35N. Lyubova, S. Ivaldi, D. Filliat.
  
  From passive to interactive object learning and recognition through self-identification on a humanoid robot, in: Autonomous Robots, 2015, 23 p. [ DOI : 10.1007/s10514-015-9445-0 ]
  
  https://hal.archives-ouvertes.fr/hal-01166110
• 36O. Mangin, D. Filliat, L. ten Bosch, P.-Y. Oudeyer.
  
  MCA-NMF: Multimodal Concept Acquisition with Non-Negative Matrix Factorization, in: PLoS ONE, October 2015, vol. 10, n^o 10, e0140732 p. [ DOI : 10.1371/journal.pone.0140732.t005 ]
  
  https://hal.archives-ouvertes.fr/hal-01137529
• 37O. Mangin, P.-Y. Oudeyer.
  
  Learning Semantic Components from Subsymbolic Multimodal Perception, in: Joint IEEE International Conference on Development and Learning an on Epigenetic Robotics (ICDL-EpiRob), Osaka, Japan, IEEE, August 2013.
  
  https://hal.inria.fr/hal-00842453
• 38A. Matricon, D. Filliat, P.-Y. Oudeyer.
  
  An Iterative Algorithm for Forward-Parameterized Skill Discovery, in: ICDL EPIROB 2016, Cergy-Pontoise, France, Proceedings of the The Sixth Joint IEEE International Conference Developmental Learning and Epigenetic Robotics, September 2016.
  
  https://hal.archives-ouvertes.fr/hal-01370820
• 39C. Moulin-Frier, S. M. Nguyen, P.-Y. Oudeyer.
  
  Self-Organization of Early Vocal Development in Infants and Machines: The Role of Intrinsic Motivation, in: Frontiers in Psychology, 2013, vol. 4, n^o 1006. [ DOI : 10.3389/fpsyg.2013.01006 ]
  
  https://hal.inria.fr/hal-00927940
• 40C. Moulin-Frier, P.-Y. Oudeyer.
  
  Exploration strategies in developmental robotics: a unified probabilistic framework, in: ICDL-Epirob - International Conference on Development and Learning, Epirob, Osaka, Japan, August 2013.
  
  https://hal.inria.fr/hal-00860641
• 41C. Moulin-Frier, P. Rouanet, P.-Y. Oudeyer.
  
  Explauto: an open-source Python library to study autonomous exploration in developmental robotics, in: ICDL-Epirob - International Conference on Development and Learning, Epirob, Genoa, Italy, October 2014.
  
  https://hal.inria.fr/hal-01061708
• 42T. Munzer, B. Piot, M. Geist, O. Pietquin, M. Lopes.
  
  Inverse Reinforcement Learning in Relational Domains, in: International Joint Conferences on Artificial Intelligence, Buenos Aires, Argentina, July 2015.
  
  https://hal.archives-ouvertes.fr/hal-01154650
• 43D. Nabil, M. Lopes, J. Gottlieb.
  
  Intrinsically motivated oculomotor exploration guided by uncertainty reduction and conditioned reinforcement in non-human primates, in: Scientific Reports, February 2016. [ DOI : 10.1038/srep20202 ]
  
  https://hal.inria.fr/hal-01266862
• 44S. M. Nguyen, S. Ivaldi, N. Lyubova, A. Droniou, D. Gerardeaux-Viret, D. Filliat, V. Padois, O. Sigaud, P.-Y. Oudeyer.
  
  Learning to recognize objects through curiosity-driven manipulation with the iCub humanoid robot, in: ICDL-EPIROB, Japan, August 2013, pp. 1–8. [ DOI : 10.1109/DevLrn.2013.6652525 ]
  
  https://hal.archives-ouvertes.fr/hal-00919674
• 45S. M. Nguyen, P.-Y. Oudeyer.
  
  Active Choice of Teachers, Learning Strategies and Goals for a Socially Guided Intrinsic Motivation Learner, in: Paladyn, September 2012, vol. 3, n^o 3, pp. 136-146. [ DOI : 10.2478/s13230-013-0110-z ]
  
  https://hal.inria.fr/hal-00936932
• 46S. M. Nguyen, P.-Y. Oudeyer.
  
  Socially Guided Intrinsically Motivated Learner, in: IEEE International Conference on Development and Learning, San Diego, United States, 2012. [ DOI : 10.1109/DevLrn.2012.6400809 ]
  
  http://hal.inria.fr/hal-00936960
• 47S. M. Nguyen, P.-Y. Oudeyer.
  
  Socially Guided Intrinsic Motivation for Robot Learning of Motor Skills, in: Autonomous Robots, March 2014, vol. 36, n^o 3, pp. 273-294. [ DOI : 10.1007/s10514-013-9339-y ]
  
  https://hal.inria.fr/hal-00936938
• 48S. Noirpoudre, D. Roy, M. Demangeat, T. Desprez, T. Segonds, P. Rouanet, D. Caselli, N. Rabault, M. Lapeyre, P.-Y. Oudeyer.
  
  Livret pédagogique : Apprendre à programmer Poppy Ergo Jr en Snap!, June 2016, 50 p, Un livret composé d'activités pédagogiques pour apprendre les bases de la programmation (programmation séquentielles, boucles, conditions, variables etc.) et des idées de défis et de projets pour appliquer les connaissances.
  
  https://hal.inria.fr/hal-01384649
• 49P.-Y. Oudeyer, F. Delaunay.
  
  Developmental exploration in the cultural evolution of lexical conventions, in: 8th International Conference on Epigenetic Robotics: Modeling Cognitive Development in Robotic Systems, Brighton, United Kingdom, 2008.
  
  https://hal.inria.fr/inria-00420303
• 50P.-Y. Oudeyer, J. Gottlieb, M. Lopes.
  
  Intrinsic motivation, curiosity and learning: theory and applications in educational technologies, in: Progress in brain research, 2016, vol. 229, pp. 257-284. [ DOI : 10.1016/bs.pbr.2016.05.005 ]
  
  https://hal.inria.fr/hal-01404278
• 51P.-Y. Oudeyer, F. Kaplan, V. Hafner.
  
  Intrinsic Motivation for Autonomous Mental Development, in: IEEE Transactions on Evolutionary Computation, January 2007, vol. 11, n^o 2, pp. 265-286. [ DOI : 10.1109/TEVC.2006.890271 ]
  
  https://hal.inria.fr/hal-00793610
• 52P.-Y. Oudeyer, F. Kaplan, V. V. Hafner.
  
  Intrinsic motivation systems for autonomous mental development, in: Evolutionary Computation, IEEE Transactions on, 2007, vol. 11, n^o 2, pp. 265–286.
• 53P.-Y. Oudeyer.
  
  On the impact of robotics in behavioral and cognitive sciences: from insect navigation to human cognitive development, in: IEEE Transactions on Autonomous Mental Development, 2010, vol. 2, n^o 1, pp. 2–16.
  
  http://hal.inria.fr/inria-00541783/en/
• 54P.-Y. Oudeyer, L. Smith.
  
  How Evolution May Work Through Curiosity-Driven Developmental Process, in: Topics in cognitive science, February 2016, vol. 8. [ DOI : 10.1111/tops.12196 ]
  
  https://hal.inria.fr/hal-01404334
• 55G. Raiola, X. Lamy, F. Stulp.
  
  Co-manipulation with Multiple Probabilistic Virtual Guides, in: IROS 2015 - International Conference on Intelligent Robots and Systems , Hamburg, Germany, September 2015, pp. 7 - 13. [ DOI : 10.1109/IROS.2015.7353107 ]
  
  https://hal.archives-ouvertes.fr/hal-01170974
• 56G. Raiola, P. Rodriguez-Ayerbe, X. Lamy, S. Tliba, F. Stulp.
  
  Parallel Guiding Virtual Fixtures: Control and Stability, in: ISIC 2015 - IEEE International Symposium on Intelligent Control, Sydney, Australia, September 2015, pp. 53 - 58. [ DOI : 10.1109/ISIC.2015.7307279 ]
  
  https://hal.archives-ouvertes.fr/hal-01250101
• 57K. J. Rohlfing, B. Wrede, A.-L. Vollmer, P.-Y. Oudeyer.
  
  An Alternative to Mapping a Word onto a Concept in Language Acquisition: Pragmatic Frames, in: Frontiers in Psychology, April 2016, vol. 7, 18 p. [ DOI : 10.3389/fpsyg.2016.00470 ]
  
  https://hal.inria.fr/hal-01404385
• 58P. Rouanet, P.-Y. Oudeyer, F. Danieau, D. Filliat.
  
  The Impact of Human-Robot Interfaces on the Learning of Visual Objects, in: IEEE Transactions on Robotics, January 2013.
  
  http://hal.inria.fr/hal-00758241
• 59D. Roy, P.-Y. Oudeyer.
  
  IniRobot et Poppy Éducation : deux kits robotiques libres pour l'enseignement de l'informatique et de la robotique, January 2016, Colloque Didapro-Didastic 6e édition, Poster.
  
  https://hal.inria.fr/hal-01263535
• 60W. Schueller, P.-Y. Oudeyer.
  
  Active Learning Strategies and Active Control of Complexity Growth in Naming Games, in: the 5th International Conference on Development and Learning and on Epigenetic Robotics, Providence, RI, United States, August 2015.
  
  https://hal.inria.fr/hal-01202654
• 61W. Schueller, P.-Y. Oudeyer.
  
  Active Control Of Complexity Growth In Naming Games: Hearer's Choice, in: The Evolution of Language: Proceedings of the 11th International Conference (EVOLANGX11), 2016.
• 62F. Stulp, B. Buchli, A. Ellmer, M. Mistry, E. Theodorou, S. Schaal.
  
  Model-free Reinforcement Learning of Impedance Control in Stochastic Force Fields, in: IEEE Transactions on Autonomous Mental Development, 2012.
• 63F. Stulp, A. Fedrizzi, L. Mösenlechner, M. Beetz.
  
  Learning and Reasoning with Action-Related Places for Robust Mobile Manipulation, in: Journal of Artificial Intelligence Research (JAIR), 2012, vol. 43, pp. 1–42.
• 64F. Stulp, J. Grizou, B. Busch, M. Lopes.
  
  Facilitating Intention Prediction for Humans by Optimizing Robot Motions, in: International Conference on Intelligent Robots and Systems (IROS), Hamburg, Germany, September 2015.
  
  https://hal.archives-ouvertes.fr/hal-01170977
• 65F. Stulp, O. Sigaud.
  
  Robot Skill Learning: From Reinforcement Learning to Evolution Strategies, in: Paladyn, 2013, vol. 4, n^o 1, pp. 49-61.
  
  https://hal.archives-ouvertes.fr/hal-00922132
• 66F. Stulp, O. Sigaud.
  
  Many regression algorithms, one unified model - A review, in: Neural Networks, 2015, 28 p. [ DOI : 10.1016/j.neunet.2015.05.005 ]
  
  https://hal.archives-ouvertes.fr/hal-01162281
• 67F. Stulp, E. Theodorou, S. Schaal.
  
  Reinforcement Learning with Sequences of Motion Primitives for Robust Manipulation, in: IEEE Transactions on Robotics, 2012, vol. 28, n^o 6, pp. 1360-1370.
• 68A.-L. Vollmer, B. Wrede, K. J. Rohlfing, P.-Y. Oudeyer.
  
  Pragmatic Frames for Teaching and Learning in Human–Robot interaction: Review and Challenges, in: Frontiers in Neurorobotics, October 2016, vol. 10, pp. 1-20. [ DOI : 10.3389/fnbot.2016.00010 ]
  
  https://hal.inria.fr/hal-01376455

Publications of the year

Articles in International Peer-Reviewed Journals

• 69B. Busch, J. Grizou, M. Lopes, F. Stulp.
  
  Learning Legible Motion from Human–Robot Interactions, in: International Journal of Social Robotics, March 2017, vol. 211, n^o 3-4, pp. 517 - 530. [ DOI : 10.1007/s12369-017-0400-4 ]
  
  https://hal.archives-ouvertes.fr/hal-01629451
• 70Y. Chen, J.-B. Bordes, D. Filliat.
  
  Comparison studies on active cross-situational object-word learning using Non-Negative Matrix Factorization and Latent Dirichlet Allocation, in: IEEE Transactions on Cognitive and Developmental Systems, 2017. [ DOI : 10.1109/TCDS.2017.2725304 ]
  
  https://hal.archives-ouvertes.fr/hal-01561168
• 71M. Couraud, D. Cattaert, F. Paclet, P.-Y. Oudeyer, A. De Rugy.
  
  Model and experiments to optimize co-adaptation in a simplified myoelectric control system, in: Journal of Neural Engineering, August 2017, pp. 1-32. [ DOI : 10.1088/1741-2552/aa87cf ]
  
  https://hal.inria.fr/hal-01677222
• 72S. Mick, D. Cattaert, F. Paclet, P.-Y. Oudeyer, A. De Rugy.
  
  Performance and Usability of Various Robotic Arm Control Modes from Human Force Signals, in: Frontiers in Neurorobotics, October 2017, vol. 11. [ DOI : 10.3389/fnbot.2017.00055 ]
  
  https://hal.inria.fr/hal-01653596
• 73C. Moulin-Frier, J. Brochard, F. Stulp, P.-Y. Oudeyer.
  
  Emergent Jaw Predominance in Vocal Development through Stochastic Optimization, in: IEEE Transactions on Cognitive and Developmental Systems, 2017, n^o 99, pp. 1-12. [ DOI : 10.1109/TCDS.2017.2704912 ]
  
  https://hal.inria.fr/hal-01578075
• 74F. Stulp, P.-Y. Oudeyer.
  
  Proximodistal Exploration in Motor Learning as an Emergent Property of Optimization, in: Developmental Science, December 2017, pp. 1-17.
  
  https://hal.inria.fr/hal-01664171

International Conferences with Proceedings

• 75B. Busch, G. Maeda, Y. Mollard, M. Demangeat, M. Lopes.
  
  Postural Optimization for an Ergonomic Human-Robot Interaction, in: IROS 2017 - IEEE/RSJ International Conference on Intelligent Robots and Systems, Vancouver, Canada, September 2017, pp. 1-8.
  
  https://hal.archives-ouvertes.fr/hal-01629426
• 76A. Delmas.
  
  Serious Game's Participatory Design and Evaluation for asthma kids, in: 29ème conférence francophone sur l'Interaction Homme-Machine, Poitiers, France, AFIHM (editor), ACM, August 2017, 12 p. [ DOI : 10.1145/3132129.3132145 ]
  
  https://hal.archives-ouvertes.fr/hal-01578648
• 77T. Desprez, S. Noirpoudre, T. Segonds, D. Caselli, D. Roy, P.-Y. Oudeyer.
  
  Poppy Ergo Jr : un kit robotique au coeur du dispositif Poppy Éducation, in: Didapro 7 2018 - DidaSTIC Colloque de didactique de l’informatique, Lausanne, Switzerland, February 2018, pp. 1-6.
  
  https://hal.inria.fr/hal-01650253
• 78S. Forestier, P.-Y. Oudeyer.
  
  A Unified Model of Speech and Tool Use Early Development, in: 39th Annual Conference of the Cognitive Science Society (CogSci 2017), London, United Kingdom, Proceedings of the 39th Annual Conference of the Cognitive Science Society, July 2017.
  
  https://hal.archives-ouvertes.fr/hal-01583301
• 79G. Maeda, M. Ewerton, T. Osa, B. Busch, J. Peters.
  
  Active Incremental Learning of Robot Movement Primitives, in: CoRL 2017 - 1st Annual Conference on Robot Learning, Mountain View, United States, November 2017, pp. 37-46.
  
  https://hal.archives-ouvertes.fr/hal-01629727
• 80T. Munzer, M. Toussaint, M. Lopes.
  
  Preference Learning on the Execution of Collaborative Human-Robot Tasks, in: ICRA 2017 - IEEE International Conference on Robotics and Automation, Singapour, Singapore, IEEE, May 2017, pp. 1-7. [ DOI : 10.1109/ICRA.2017.7989108 ]
  
  https://hal.archives-ouvertes.fr/hal-01644014
• 81S. Noirpoudre, D. Roy, T. Desprez, T. Segonds, D. Caselli, P.-Y. Oudeyer.
  
  Poppy Education : un dispositif robotique open source pour l'enseignement de l'informatique et de la robotique, in: EIAH 2017 - Environnements Informatiques pour l'Apprentissage Humain, Strasbourg, France, June 2017, 8 p.
  
  https://hal.inria.fr/hal-01517941

Conferences without Proceedings

• 82T. Munzer, Y. Mollard, M. Lopes.
  
  Impact of Robot Initiative on Human-Robot Collaboration, in: HRI 2017 - ACM/IEEE International Conference on Human-Robot Interaction, Vienne, Austria, ACM, March 2017, pp. 217-218. [ DOI : 10.1145/3029798.3038373 ]
  
  https://hal.archives-ouvertes.fr/hal-01644010

Scientific Popularization

• 83S. Noirpoudre.
  
  Atelier Poppy Ergo Jr au CERN, January 2017, pp. 1-6.
  
  https://hal.inria.fr/hal-01658632
• 84S. Noirpoudre.
  
  Robotic workshop at CERN, January 2017, pp. 1-7.
  
  https://hal.inria.fr/hal-01658664
• 85S. Noirpoudre, K. Schindowsky.
  
  Poppy Education at EIDOS 64 : The Digital Practice Forum for Education, February 2017, pp. 1-5.
  
  https://hal.inria.fr/hal-01658760
• 86K. Schindowsky.
  
  Des roues pour le robot Poppy Torso : 2ème édition du projet étudiant de l'ENSAM, June 2017.
  
  https://hal.inria.fr/hal-01660847
• 87K. Schindowsky.
  
  Utilisation de la plateforme Poppy pour un projet étudiant : 4 robots Poppy Torso modifiés par les élèves du campus de Bordeaux-Talence se sont affrontés dans le grand amphi. Une compétition d’un nouveau genre comprenant des figures libres et des figures imposées, April 2017.
  
  https://hal.inria.fr/hal-01660841
• 88S. Soulard, K. Schindowsky.
  
  Le port de Rotterdam simulé dans une salle de classe avec le robot Poppy Ergo Jr, March 2017.
  
  https://hal.inria.fr/hal-01660832

Other Publications

• 89S. Forestier, Y. Mollard, P.-Y. Oudeyer.
  
  Intrinsically Motivated Goal Exploration Processes with Automatic Curriculum Learning, November 2017, working paper or preprint.
  
  https://hal.archives-ouvertes.fr/hal-01651233
• 90T. Lesort, M. Seurin, X. Li, N. D. Rodríguez, D. Filliat.
  
  Unsupervised state representation learning with robotic priors: a robustness benchmark, November 2017, https://arxiv.org/abs/1709.05185 - ICRA 2018 submission.
  
  https://hal.archives-ouvertes.fr/hal-01644423

References in notes

• 91L. Steels, R. Brooks (editors)
  
  The Artificial Life Route to Artificial Intelligence: Building Embodied, Situated Agents, L. Erlbaum Associates Inc., Hillsdale, NJ, USA, 1995.
• 92M. Al-Motlaq, K. Sellick.
  
  Development and validation of an asthma knowledge test for children 8–10 years of age, in: Child: Care, health and development, 2011, vol. 37, n^o 1, pp. 123–128.
• 93B. A. Anderson, P. A. Laurent, S. Yantis.
  
  Value-driven attentional capture, in: Proceedings of the National Academy of Sciences, 2011, vol. 108, n^o 25, pp. 10367–10371.
• 94B. Argall, S. Chernova, M. Veloso.
  
  A Survey of Robot Learning from Demonstration, in: Robotics and Autonomous Systems, 2009, vol. 57, n^o 5, pp. 469–483.
• 95M. Asada, S. Noda, S. Tawaratsumida, K. Hosoda.
  
  Purposive Behavior Acquisition On A Real Robot By Vision-Based Reinforcement Learning, in: Machine Learning, 1996, vol. 23, pp. 279-303.
• 96G. Baldassarre, M. Mirolli.
  
  Intrinsically Motivated Learning in Natural and Artificial Systems, Springer, 2013.
• 97A. Baronchelli.
  
  Statistical mechanics approach to language games, PhD thesis,” Sapienza” Univ. of Rome, 2006.
• 98A. Barto, M. Mirolli, G. Baldassarre.
  
  Novelty or surprise?, in: Frontiers in psychology, 2013, vol. 4.
• 99A. Barto, S. Singh, N. Chentanez.
  
  Intrinsically Motivated Learning of Hierarchical Collections of Skills, in: Proceedings of the 3rd International Conference on Development and Learning (ICDL 2004), Salk Institute, San Diego, 2004.
• 100D. Berlyne.
  
  Conflict, Arousal and Curiosity, McGraw-Hill, 1960.
• 101C. Breazeal.
  
  Designing sociable robots, The MIT Press, 2004.
• 102A. Brock, J.-L. Vinot, B. Oriola, S. Kammoun, P. Truillet, C. Jouffrais.
  
  Méthodes et outils de conception participative avec des utilisateurs non-voyants, in: Proceedings of the 22nd Conference on l'Interaction Homme-Machine, ACM, 2010, pp. 65–72.
• 103J. Brooke.
  
  SUS-A quick and dirty usability scale, in: Usability evaluation in industry, 1996, vol. 189, n^o 194, pp. 4–7.
• 104R. Brooks, C. Breazeal, R. Irie, C. C. Kemp, B. Scassellati, M. Williamson.
  
  Alternative essences of intelligence, in: Proceedings of 15th National Conference on Artificial Intelligence (AAAI-98), AAAI Press, 1998, pp. 961–968.
• 105A. Cangelosi, G. Metta, G. Sagerer, S. Nolfi, C. Nehaniv, K. Fischer, J. Tani, T. Belpaeme, G. Sandini, F. Nori.
  
  Integration of action and language knowledge: A roadmap for developmental robotics, in: Autonomous Mental Development, IEEE Transactions on, 2010, vol. 2, n^o 3, pp. 167–195.
• 106D. Centola, A. Baronchelli.
  
  The spontaneous emergence of conventions: An experimental study of cultural evolution, in: Proceedings of the National Academy of Sciences, 2015, vol. 112, n^o 7, pp. 1989–1994.
• 107A. Clark.
  
  Mindware: An Introduction to the Philosophy of Cognitive Science, Oxford University Press, 2001.
• 108D. Cohn, Z. Ghahramani, M. Jordan.
  
  Active learning with statistical models, in: Journal of artificial intelligence research, 1996, vol. 4, pp. 129–145.
• 109M. Cornudella, P. Van Eecke, R. Van Trijp.
  
  How Intrinsic Motivation can Speed Up Language Emergence, in: Proceedings of the European Conference on Artificial Life, 2015, pp. 571–578.
• 110W. Croft, D. Cruse.
  
  Cognitive Linguistics, Cambridge Textbooks in Linguistics, Cambridge University Press, 2004.
• 111M. Csikszenthmihalyi.
  
  Flow-the psychology of optimal experience, Harper Perennial, 1991.
• 112P. Dayan, W. Belleine.
  
  Reward, motivation and reinforcement learning, in: Neuron, 2002, vol. 36, pp. 285–298.
• 113E. Deci, R. Ryan.
  
  Intrinsic Motivation and Self-Determination in Human Behavior, Plenum Press, 1985.
• 114J. Elman.
  
  Learning and development in neural networks: The importance of starting small, in: Cognition, 1993, vol. 48, pp. 71–99.
• 115S. B. Flagel, H. Akil, T. E. Robinson.
  
  Individual differences in the attribution of incentive salience to reward-related cues: Implications for addiction, in: Neuropharmacology, 2009, vol. 56, pp. 139–148.
• 116M. C. Frank, N. D. Goodman.
  
  Predicting pragmatic reasoning in language games, in: Science, 2012, vol. 336, n^o 6084, pp. 998–998.
• 117Y. Gal.
  
  Uncertainty in Deep Learning, University of Cambridge, 2016, unpublished thesis.
• 118B. Galantucci, S. Garrod.
  
  Experimental semiotics: a review, in: Frontiers in human neuroscience, 2011, vol. 5, 11 p.
• 119G. Gordon, C. Breazeal, S. Engel.
  
  Can children catch curiosity from a social robot?, in: Proceedings of the Tenth Annual ACM/IEEE International Conference on Human-Robot Interaction, ACM, 2015, pp. 91–98.
• 120J. Gottlieb, P.-Y. Oudeyer, M. Lopes, A. Baranes.
  
  Information-seeking, curiosity, and attention: computational and neural mechanisms, in: Trends in cognitive sciences, 2013, vol. 17, n^o 11, pp. 585–593.
• 121S. Harnad.
  
  The symbol grounding problem, in: Physica D, 1990, vol. 40, pp. 335–346.
• 122M. Hasenjager, H. Ritter.
  
  Active learning in neural networks, Physica-Verlag GmbH, Heidelberg, Germany, Germany, 2002, pp. 137–169.
• 123J. Haugeland.
  
  Artificial Intelligence: the very idea, The MIT Press, Cambridge, MA, USA, 1985.
• 124S. Hignett, L. McAtamney.
  
  Rapid entire body assessment (REBA), in: Applied ergonomics, 2000, vol. 31, n^o 2, pp. 201–205.
• 125J.-C. Horvitz.
  
  Mesolimbocortical and nigrostriatal dopamine responses to salient non-reward events, in: Neuroscience, 2000, vol. 96, n^o 4, pp. 651-656.
• 126X. Huang, J. Weng.
  
  Novelty and reinforcement learning in the value system of developmental robots, in: Proceedings of the 2nd international workshop on Epigenetic Robotics : Modeling cognitive development in robotic systems, C. Prince, Y. Demiris, Y. Marom, H. Kozima, C. Balkenius (editors), Lund University Cognitive Studies 94, 2002, pp. 47–55.
• 127S. Ivaldi, N. Lyubova, D. Gérardeaux-Viret, A. Droniou, S. Anzalone, M. Chetouani, D. Filliat, O. Sigaud.
  
  Perception and human interaction for developmental learning of objects and affordances, in: Proc. of the 12th IEEE-RAS International Conference on Humanoid Robots - HUMANOIDS, Japan, 2012, forthcoming.
  
  http://hal.inria.fr/hal-00755297
• 128M. Johnson.
  
  Developmental Cognitive Neuroscience, 2nd, Blackwell publishing, 2005.
• 129R. Jonschkowski, O. Brock.
  
  Learning state representations with robotic priors, in: Autonomous Robots, 2015, vol. 39, n^o 3, pp. 407–428.
• 130F. Kaplan, P.-Y. Oudeyer, B. Bergen.
  
  Computational models in the debate over language learnability, in: Infant and Child Development, 2008, vol. 17, n^o 1, pp. 55–80.
• 131S. Kauffman, N. Santa Fe Institute (Santa Fe.
  
  Investigations: The Nature of Autonomous Agents and the Worlds They Mutually Create, SFI working papers, Santa Fe Institute, 1996.
  
  https://books.google.fr/books?id=IgiOPwAACAAJ
• 132C. Kidd, B. Hayden.
  
  The psychology and neuroscience of curiosity, in: Neuron (in press), 2015.
• 133S. Kirby, T. Griffiths, K. Smith.
  
  Iterated learning and the evolution of language, in: Current opinion in neurobiology, 2014, vol. 28, pp. 108–114.
• 134W. B. Knox, P. Stone.
  
  Combining manual feedback with subsequent MDP reward signals for reinforcement learning, in: Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems (AAMAS'10), 2010, pp. 5–12.
• 135C. Lallemand, V. Koenig, G. Gronier, R. Martin.
  
  Création et validation d’une version française du questionnaire AttrakDiff pour l’évaluation de l’expérience utilisateur des systèmes interactifs, in: Revue Européenne de Psychologie Appliquée/European Review of Applied Psychology, 2015, vol. 65, n^o 5, pp. 239–252.
• 136L. Li, W. Chu, J. Langford, R. E. Schapire.
  
  A Contextual-Bandit Approach to Personalized News Article Recommendation, in: CoRR, 2010, vol. abs/1003.0146.
  
  http://arxiv.org/abs/1003.0146
• 137G. Loewenstein.
  
  The psychology of curiosity: A review and reinterpretation, in: Psychological bulletin, 1994, vol. 116, n^o 1, 75 p.
• 138M. Lopes, T. Cederborg, P.-Y. Oudeyer.
  
  Simultaneous Acquisition of Task and Feedback Models, in: Development and Learning (ICDL), 2011 IEEE International Conference on, Germany, 2011, pp. 1 - 7. [ DOI : 10.1109/DEVLRN.2011.6037359 ]
  
  http://hal.inria.fr/hal-00636166/en
• 139M. Lopes, L. Montesano.
  
  Active Learning for Autonomous Intelligent Agents: Exploration, Curiosity, and Interaction, in: CoRR, 2014, vol. abs/1403.1, 40 p.
• 140V. Loreto, A. Baronchelli, A. Mukherjee, A. Puglisi, F. Tria.
  
  Statistical physics of language dynamics, in: Journal of Statistical Mechanics: Theory and Experiment, 2011, vol. 2011, n^o 04, P04006 p. [ DOI : 10.1088/1742-5468/2011/04/P04006 ]
• 141M. Lungarella, G. Metta, R. Pfeifer, G. Sandini.
  
  Developmental Robotics: A Survey, in: Connection Science, 2003, vol. 15, n^o 4, pp. 151-190.
• 142S. MacFarlane, G. Sim, M. Horton.
  
  Assessing usability and fun in educational software, in: Proceedings of the 2005 conference on Interaction design and children, ACM, 2005, pp. 103–109.
• 143J. Marshall, D. Blank, L. Meeden.
  
  An Emergent Framework for Self-Motivation in Developmental Robotics, in: Proceedings of the 3rd International Conference on Development and Learning (ICDL 2004), Salk Institute, San Diego, 2004.
• 144M. Mason, M. Lopes.
  
  Robot Self-Initiative and Personalization by Learning through Repeated Interactions, in: 6th ACM/IEEE International Conference on Human-Robot, Switzerland, 2011. [ DOI : 10.1145/1957656.1957814 ]
  
  http://hal.inria.fr/hal-00636164/en
• 145P. Miller.
  
  Theories of developmental psychology, 4th, New York: Worth, 2001.
• 146M. Mirolli, G. Baldassarre.
  
  Functions and mechanisms of intrinsic motivations, in: Intrinsically Motivated Learning in Natural and Artificial Systems, Springer, 2013, pp. 49–72.
• 147S. M. Nguyen, A. Baranes, P.-Y. Oudeyer.
  
  Bootstrapping Intrinsically Motivated Learning with Human Demonstrations, in: IEEE International Conference on Development and Learning, Frankfurt, Germany, 2011.
  
  http://hal.inria.fr/hal-00645986/en
• 148S. M. Nguyen, A. Baranes, P.-Y. Oudeyer.
  
  Constraining the Size Growth of the Task Space with Socially Guided Intrinsic Motivation using Demonstrations., in: IJCAI Workshop on Agents Learning Interactively from Human Teachers (ALIHT), Barcelona, Spain, 2011.
  
  http://hal.inria.fr/hal-00645995/en
• 149P.-Y. Oudeyer, F. Kaplan, V. Hafner.
  
  Intrinsic Motivation for Autonomous Mental Development, in: IEEE Transactions on Evolutionary Computation, January 2007, vol. 11, n^o 2, pp. 265-286. [ DOI : 10.1109/TEVC.2006.890271 ]
  
  https://hal.inria.fr/hal-00793610
• 150P.-Y. Oudeyer, F. Kaplan, V. Hafner.
  
  Intrinsic Motivation Systems for Autonomous Mental Development, in: IEEE Transactions on Evolutionary Computation, 2007, vol. 11, n^o 1, pp. 265–286.
  
  http://www.pyoudeyer.com/ims.pdf
• 151P.-Y. Oudeyer, F. Kaplan.
  
  Intelligent adaptive curiosity: a source of self-development, in: Proceedings of the 4th International Workshop on Epigenetic Robotics, L. Berthouze, H. Kozima, C. Prince, G. Sandini, G. Stojanov, G. Metta, C. Balkenius (editors), Lund University Cognitive Studies, 2004, vol. 117, pp. 127–130.
• 152P.-Y. Oudeyer, F. Kaplan.
  
  What is intrinsic motivation? A typology of computational approaches, in: Frontiers in Neurorobotics, 2007, vol. 1, n^o 1.
• 153P.-Y. Oudeyer.
  
  Sur les interactions entre la robotique et les sciences de l'esprit et du comportement, in: Informatique et Sciences Cognitives : influences ou confluences ?, C. Garbay, D. Kaiser (editors), Presses Universitaires de France, 2009.
  
  http://hal.inria.fr/inria-00420309/en/
• 154P.-Y. Oudeyer.
  
  Developmental Learning of Sensorimotor Models for Control in Robotics, in: SIAM News, September 2014, vol. 47, n^o 7.
  
  https://hal.inria.fr/hal-01061633
• 155P.-Y. Oudeyer.
  
  L'auto-organisation dans l'évolution de la parole, in: Parole et Musique: Aux origines du dialogue humain, Colloque annuel du Collège de France, S. Dehaene, C. Petit (editors), Odile Jacob, 2009, pp. 83-112.
  
  http://hal.inria.fr/inria-00446908/en/
• 156M. Pelz, S. T. Piantadosi, C. Kidd.
  
  The dynamics of idealized attention in complex learning environments, in: IEEE International Conference on Development and Learning and on Epigenetic Robotics, 2015.
• 157J. C. Read, S. MacFarlane.
  
  Using the fun toolkit and other survey methods to gather opinions in child computer interaction, in: Proceedings of the 2006 conference on Interaction design and children, ACM, 2006, pp. 81–88.
• 158A. Revel, J. Nadel.
  
  How to build an imitator?, in: Imitation and Social Learning in Robots, Humans and Animals: Behavioural, Social and Communicative Dimensions, K. Dautenhahn, C. Nehaniv (editors), Cambridge University Press, 2004.
• 159E. F. Risko, N. C. Anderson, S. Lanthier, A. Kingstone.
  
  Curious eyes: Individual differences in personality predict eye movement behavior in scene-viewing, in: Cognition, 2012, vol. 122, n^o 1, pp. 86–90.
• 160V. G. Santucci, G. Baldassarre, M. Mirolli.
  
  Which is the best intrinsic motivation signal for learning multiple skills?, in: Frontiers in neurorobotics, 2013, vol. 7.
• 161T. Schatz, P.-Y. Oudeyer.
  
  Learning motor dependent Crutchfield's information distance to anticipate changes in the topology of sensory body maps, in: IEEE International Conference on Learning and Development, Chine Shangai, 2009.
  
  http://hal.inria.fr/inria-00420186/en/
• 162M. Schembri, M. Mirolli, G. Baldassarre.
  
  Evolving internal reinforcers for an intrinsically motivated reinforcement-learning robot, in: IEEE 6th International Conference on Development and Learning, 2007. ICDL 2007., July 2007, pp. 282-287.
  
  http://dx.doi.org/10.1109/DEVLRN.2007.4354052
• 163J. Schmidhuber.
  
  Curious Model-Building Control Systems, in: Proceedings of the International Joint Conference on Neural Networks, Singapore, IEEE press, 1991, vol. 2, pp. 1458–1463.
• 164W. Schultz, P. Dayan, P. Montague.
  
  A neural substrate of prediction and reward, in: Science, 1997, vol. 275, pp. 1593-1599.
• 165L. Steels, F. Kaplan, A. McIntyre, J. Van Looveren.
  
  Crucial factors in the origins of word-meaning, in: The transition to language, 2002, vol. 12, pp. 252–271.
• 166L. Steels.
  
  Language games for autonomous robots, in: Intelligent Systems, IEEE, 2001, vol. 16, n^o 5, pp. 16–22.
• 167L. Steels.
  
  The Autotelic Principle, in: Science, 2004, vol. 3139, pp. 1–16. [ DOI : 10.1007/b99075 ]
• 168E. Sumner, E. DeAngelis, M. Hyatt, N. Goodman, C. Kidd.
  
  Toddlers Always Get the Last Word: Recency biases in early verbal behavior, in: Proceedings of the 37th Annual Meeting of the Cognitive Science Society, 2015.
• 169E. Thelen, L. B. Smith.
  
  A dynamic systems approach to the development of cognition and action, MIT Press, Cambridge, MA, 1994.
• 170A. L. Thomaz, C. Breazeal.
  
  Teachable robots: Understanding human teaching behavior to build more effective robot learners, in: Artificial Intelligence Journal, 2008, vol. 172, pp. 716-737.
• 171M. Toussaint.
  
  Logic-Geometric Programming: An Optimization-Based Approach to Combined Task and Motion Planning., in: IJCAI, 2015, pp. 1930–1936.
• 172F. Tria, V. Loreto, V. D. P. Servedio, S. H. Strogatz.
  
  The dynamics of correlated novelties, in: Scientific reports, 2014, vol. 4.
• 173A. Turing.
  
  Computing machinery and intelligence, in: Mind, 1950, vol. 59, pp. 433-460.
• 174M. R. Uncapher, M. K. Thieu, A. D. Wagner.
  
  Media multitasking and memory: Differences in working memory and long-term memory, in: Psychonomic bulletin & review, 2015, pp. 1–8.
• 175R. J. Vallerand, L. G. Pelletier, M. R. Blais, N. M. Briere, C. Senecal, E. F. Vallieres.
  
  The Academic Motivation Scale: A measure of intrinsic, extrinsic, and amotivation in education, in: Educational and psychological measurement, 1992, vol. 52, n^o 4, pp. 1003–1017.
• 176F. Varela, E. Thompson, E. Rosch.
  
  The embodied mind : Cognitive science and human experience, MIT Press, Cambridge, MA, 1991.
• 177P. Wellens.
  
  Adaptive Strategies in the Emergence of Lexical Systems, Vrije Universiteit Brussel, Brussels, 2012.
  
  http://ai.vub.ac.be/publications/918
• 178J. Weng, J. McClelland, A. Pentland, O. Sporns, I. Stockman, M. Sur, E. Thelen.
  
  Autonomous mental development by robots and animals, in: Science, 2001, vol. 291, pp. 599-600.