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Bibliography

Major publications by the team in recent years
  • 1A. Angeli, D. Filliat, S. Doncieux, J. Meyer.

    Fast and incremental method for loop-closure detection using bags of visual words, in: Robotics, IEEE Transactions on, 2008, vol. 24, no 5, pp. 1027–1037.
  • 2A. Baranes, P.-Y. Oudeyer.

    RIAC: Robust Intrinsically Motivated Exploration and Active Learning, in: IEEE Trans. on Auto. Ment. Dev., 2009, vol. 1, no 3, pp. 155-169.

    http://www.pyoudeyer.com/TAMDBaranesOudeyer09.pdf
  • 3A. Baranes, P.-Y. Oudeyer.

    Active learning of inverse models with intrinsically motivated goal exploration in robots, in: Robotics and Autonomous Systems, 2013, vol. 61, no 1, pp. 49 - 73. [ DOI : 10.1016/j.robot.2012.05.008 ]

    http://www.pyoudeyer.com/RAS-SAGG-RIAC-2012.pdf
  • 4J. Buchli, F. Stulp, E. Theodorou, S. Schaal.

    Learning Variable Impedance Control, in: International Journal of Robotics Research, 2011, vol. 30, no 7, pp. 820-833.

    http://ijr.sagepub.com/content/early/2011/03/31/0278364911402527
  • 5T. Degris, O. Sigaud, P. Wuillemin.

    Learning the Structure of Factored Markov Decision Processes in Reinforcement Learning Problems, in: Proceedings of the 23rd International Conference on Machine learning (ICML), 2006, pp. 257–264.
  • 6T. Degris, M. White, R. Sutton.

    Off-Policy Actor-Critic, in: International Conference on Machine Learning, 2012.

    http://hal.inria.fr/hal-00764021
  • 7D. Filliat.

    A visual bag of words method for interactive qualitative localization and mapping, in: Robotics and Automation, 2007 IEEE International Conference on, IEEE, 2007, pp. 3921–3926.
  • 8A. 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
  • 9A. 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, no 1.

    http://hal.archives-ouvertes.fr/hal-00647809/en/
  • 10J. 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, no 11, pp. 585-93. [ DOI : 10.1016/j.tics.2013.09.001 ]

    http://hal.inria.fr/hal-00913646
  • 11M. 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
  • 12M. 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
  • 13M. Lopes, F. Melo, L. Montesano.

    Active learning for reward estimation in inverse reinforcement learning, in: Machine Learning and Knowledge Discovery in Databases, 2009, pp. 31–46.
  • 14L. Montesano, M. Lopes, A. Bernardino, J. Santos-Victor.

    Learning Object Affordances: From Sensory–Motor Coordination to Imitation, in: Robotics, IEEE Transactions on, 2008, vol. 24, no 1, pp. 15–26.
  • 15S. M. Nguyen, A. Baranes, P.-Y. Oudeyer.

    Bootstrapping Intrinsically Motivated Learning with Human Demonstrations, in: proceedings of the IEEE International Conference on Development and Learning, Frankfurt, Allemagne, 2011, ERC Grant EXPLORERS 240007.

    http://hal.archives-ouvertes.fr/hal-00645986
  • 16P.-Y. Oudeyer, F. Kaplan, V. Hafner.

    Intrinsic Motivation Systems for Autonomous Mental Development, in: IEEE Transactions on Evolutionary Computation, 2007, vol. 11, no 1, pp. 265–286.

    http://www.pyoudeyer.com/ims.pdf
  • 17P.-Y. Oudeyer.

    Self-Organization in the Evolution of Speech, Studies in the Evolution of Language, Oxford University Press, 2006.
  • 18P.-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, no 1, pp. 2–16.

    http://hal.inria.fr/inria-00541783/en/
  • 19P. 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
  • 20F. 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.
  • 21F. 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.
  • 22F. Stulp, E. Theodorou, S. Schaal.

    Reinforcement Learning with Sequences of Motion Primitives for Robust Manipulation, in: IEEE Transactions on Robotics, 2012, vol. 28, no 6, pp. 1360-1370.
Publications of the year

Doctoral Dissertations and Habilitation Theses

Articles in International Peer-Reviewed Journals

  • 27A. 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
  • 28S. Bazeille, E. Battesti, D. Filliat.

    A Light Visual Mapping and Navigation Framework for Low-Cost Robots, in: Journal of Intelligent Systems, February 2015, 27 p. [ DOI : 10.1515/jisys-2014-0116 ]

    https://hal-ensta.archives-ouvertes.fr/hal-01122633
  • 29B. 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, no 2, pp. 20–48.

    https://hal.inria.fr/hal-00913669
  • 30I. 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
  • 31N. 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
  • 32O. 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, no 10, e0140732. [ DOI : 10.1371/journal.pone.0140732.t005 ]

    https://hal.archives-ouvertes.fr/hal-01137529
  • 33C. Moulin-Frier, J. Diard, J.-L. Schwartz, P. Bessière.

    COSMO (“Communicating about Objects using Sensory–Motor Operations”): A Bayesian modeling framework for studying speech communication and the emergence of phonological systems, in: Journal of Phonetics, November 2015, vol. 53, pp. 5–41. [ DOI : 10.1016/j.wocn.2015.06.001 ]

    https://hal.archives-ouvertes.fr/hal-01230175
  • 34P.-Y. Oudeyer.

    Open challenges in understanding development and evolution of speech forms: The roles of embodied self-organization, motivation and active exploration, in: Journal of Phonetics, November 2015, vol. 53, 5 p. [ DOI : 10.1016/j.wocn.2015.09.001 ]

    https://hal.inria.fr/hal-01250777
  • 35J.-L. Schwartz, C. Moulin-Frier, P.-Y. Oudeyer.

    On the cognitive nature of speech sound systems, in: Journal of Phonetics, November 2015, vol. 53, pp. 1-4.

    https://hal.archives-ouvertes.fr/hal-01222752
  • 36D. P. Stark, J. Richard, S. Charlot, B. Clément, R. Ellis, B. Siana, B. Robertson, M. Schenker, J. Gutkin, A. Wofford.

    Spectroscopic detections of C III] λ1909 Å at z ≃ 6-7: a new probe of early star-forming galaxies and cosmic reionization, in: Monthly Notices of the Royal Astronomical Society, June 2015, vol. 450, pp. 1846 - 1855. [ DOI : 10.1093/mnras/stv688 ]

    https://hal.archives-ouvertes.fr/hal-01149004
  • 37F. 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
  • 38A.-L. Vollmer, K. J. Rohlfing, B. Wrede, A. Cangelosi.

    Alignment to the Actions of a Robot, in: International Journal of Social Robotics, 2015. [ DOI : 10.1007/s12369-014-0252-0 ]

    https://hal.inria.fr/hal-01249226

International Conferences with Proceedings

  • 39A. Baisero, Y. Mollard, M. Lopes, M. Toussaint, I. Lutkebohle.

    Temporal Segmentation of Pair-Wise Interaction Phases in Sequential Manipulation Demonstrations, in: Intelligent Robots and Systems (IROS), 2015 IEEE/RSJ International Conference on, Hamburg, Germany, September 2015. [ DOI : 10.1109/IROS.2015.7353415 ]

    https://hal.inria.fr/hal-01246455
  • 40F. Benureau, P.-Y. Oudeyer.

    Diversity-driven selection of exploration strategies in multi-armed bandits, in: IEEE International Conference on Development and Learning and Epigenetic Robotics, Providence, United States, August 2015. [ DOI : 10.1109/DEVLRN.2015.7346130 ]

    https://hal.inria.fr/hal-01251060
  • 41Y. 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
  • 42C. Craye, D. Filliat, J.-F. Goudou.

    Apprentissage incrémental de la saillance visuelle pour des applications robotique, in: Journées francophones des jeunes chercheurs en vision par ordinateur, Amiens, France, June 2015.

    https://hal.archives-ouvertes.fr/hal-01161848
  • 43C. Craye, D. Filliat, J.-F. Goudou.

    Exploration Strategies for Incremental Learning of Object-Based Visual Saliency, in: ICDL-EPIROB, Providence, United States, August 2015.

    https://hal.archives-ouvertes.fr/hal-01170532
  • 44A. Gepperth, T. Hecht, M. Lefort, U. Körner.

    Biologically inspired incremental learning for high-dimensional spaces, in: International Conference on Development and Learning (ICDL), Providence, United States, September 2015. [ DOI : 10.1109/DEVLRN.2015.7346155 ]

    https://hal.archives-ouvertes.fr/hal-01250961
  • 45T. Hecht, A. Gepperth.

    A generative-discriminative learning model for noisy information fusion, in: International Conference on Development and Learning (ICDL), Providence, United States, August 2015. [ DOI : 10.1109/DEVLRN.2015.7346148 ]

    https://hal.archives-ouvertes.fr/hal-01250967
  • 46T. Kopinski, S. Magand, A. Gepperth, U. Handmann.

    A light-weight real-time applicable hand gesture recognition system for automotive applications, in: IEEE International Symposium on Intelligent Vehicles (IV), Seoul, South Korea, June 2015, pp. 336-342. [ DOI : 10.1109/IVS.2015.7225708 ]

    https://hal-ensta.archives-ouvertes.fr/hal-01251413
  • 47M. Lefort, A. Gepperth.

    Active learning of local predictable representations with artificial curiosity, in: International Conference on Development and Learning and Epigenetic Robotics (ICDL-Epirob), Providence, United States, August 2015.

    https://hal.archives-ouvertes.fr/hal-01205619
  • 48M. Lefort, A. Gepperth.

    Learning of local predictable representations in partially learnable environments, in: The International Joint Conference on Neural Networks (IJCNN), Killarney, Ireland, July 2015.

    https://hal.archives-ouvertes.fr/hal-01205611
  • 49T. 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
  • 50D. Roy, G. Gerber, S. Magnenat, F. Riedo, M. Chevalier, P.-Y. Oudeyer, F. Mondada.

    IniRobot : a pedagogical kit to initiate children to concepts of robotics and computer science, in: RIE 2015, Yverdon-Les-Bains, Switzerland, May 2015.

    https://hal.inria.fr/hal-01144435

Conferences without Proceedings

  • 51M. Duflot, M. Quinson, F. Masseglia, D. Roy, J. Vaubourg, T. Viéville.

    When sharing computer science with everyone also helps avoiding digital prejudices, in: Scratch2015AMS, Amsterdam, Netherlands, August 2015.

    https://hal.inria.fr/hal-01154767
  • 52A. Gepperth, M. Lefort, T. Hecht, U. Körner.

    Resource-efficient incremental learning in very high dimensions, in: European Symposium on Artificial Neural Networks (ESANN), Bruges, Belgium, April 2015.

    https://hal.archives-ouvertes.fr/hal-01251015
  • 53T. Hecht, M. Lefort, A. Gepperth.

    Using self-organizing maps for regression: the importance of the output function, in: European Symposium on Artificial Neural Networks (ESANN), Bruges, Belgium, April 2015.

    https://hal.archives-ouvertes.fr/hal-01251011
  • 54T. Kopinski, A. Gepperth, U. Handmann.

    A simple technique for improving multi-class classification with neural networks, in: European Symposium on artificial neural networks (ESANN), Bruges, Belgium, June 2015.

    https://hal.archives-ouvertes.fr/hal-01251009
  • 55T. Kopinski, S. Magand, U. Handmann, A. Gepperth.

    A pragmatic approach to multi-class classification, in: European Symposium on artificial neural networks (ESANN), Bruges, Belgium, April 2015. [ DOI : 10.1109/IJCNN.2015.7280768 ]

    https://hal-ensta.archives-ouvertes.fr/hal-01251382
  • 56Y. Mollard, T. Munzer, A. Baisero, M. Toussaint, M. Lopes.

    Robot Programming from Demonstration, Feedback and Transfer, in: IEEE/RSJ International Conference on Intelligent Robots and Systems, Hamburg, Germany, September 2015.

    https://hal.inria.fr/hal-01203350
  • 57G. 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
  • 58G. 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
  • 59W. 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
  • 60F. 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

Scientific Books (or Scientific Book chapters)

  • 61J.-L. Schwartz, C. Moulin-Frier, P.-Y. Oudeyer.

    On the cognitive nature of speech sound systems, Journal of Phonetics - Special issue: "On the cognitive nature of speech sound systems", Elsevier, November 2015, vol. 53, pp. 1-175.

    https://hal.archives-ouvertes.fr/hal-01222761

Internal Reports

  • 62D. Roy.

    Personnalisation automatique des parcours d’apprentissage dans les Systèmes Tuteurs Intelligents, Inria Bordeaux Sud-Ouest, February 2015.

    https://hal.inria.fr/hal-01144515

Scientific Popularization

  • 63J. Audouze, G. Chapouthier, D. Laming, P.-Y. Oudeyer.

    Mondes Mosaiques, CNRS Editions, October 2015, 216 p.

    https://hal.inria.fr/hal-01250693
  • 64P.-Y. Oudeyer.

    What do we learn about development from baby robots?, January 2015, Article explaining to a wide audience that building and experimenting with robots modeling the growing infant brain and body is crucial for understanding pattern formation in development viewed as a complex dynamical system.

    https://hal.inria.fr/hal-01107240

Other Publications

  • 65S. Forestier, P.-Y. Oudeyer.

    Towards hierarchical curiosity-driven exploration of sensorimotor models, August 2015, 5th International Conference on Development and Learning and on Epigenetic Robotics (ICDL-EpiRob), Poster. [ DOI : 10.1109/DEVLRN.2015.7346146 ]

    https://hal.archives-ouvertes.fr/hal-01250424
  • 66M. Lopes.

    Autonomous Learning in Intelligent Agents and Robots, September 2015, Habilitation a Diriger des Recherches, Universite de Bordeaux.

    https://hal.inria.fr/hal-01246812
  • 67P.-Y. Oudeyer.

    Building Up the Community: Interdisciplinary Bridges and Open Science, May 2015, Editorial of the IEEE CIS Newsletter on Cognitive and Developmental Systems, 12(1).

    https://hal.inria.fr/hal-01250784
  • 68P.-Y. Oudeyer.

    Explaining and Communicating About Developmental Systems: How To Change Representations, December 2015, 2 p, Editorial of IEEE CIS Newsletter on Cognitive and Developmental Systems, 12(2).

    https://hal.inria.fr/hal-01250781
References in notes
  • 69L. Steels, R. Brooks (editors)

    The Artificial Life Route to Artificial Intelligence: Building Embodied, Situated Agents, L. Erlbaum Associates Inc., Hillsdale, NJ, USA, 1995.
  • 70B. A. Anderson, P. A. Laurent, S. Yantis.

    Value-driven attentional capture, in: Proceedings of the National Academy of Sciences, 2011, vol. 108, no 25, pp. 10367–10371.
  • 71B. Argall, S. Chernova, M. Veloso.

    A Survey of Robot Learning from Demonstration, in: Robotics and Autonomous Systems, 2009, vol. 57, no 5, pp. 469–483.
  • 72M. 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.
  • 73A. 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, no 1, pp. 69-73. [ DOI : 10.1016/j.robot.2012.05.008 ]

    https://hal.inria.fr/hal-00788440
  • 74A. Barto, M. Mirolli, G. Baldassarre.

    Novelty or surprise?, in: Frontiers in psychology, 2013, vol. 4.
  • 75A. 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.
  • 76D. Berlyne.

    Conflict, Arousal and Curiosity, McGraw-Hill, 1960.
  • 77C. Breazeal.

    Designing sociable robots, The MIT Press, 2004.
  • 78R. 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.
  • 79A. 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, no 3, pp. 167–195.
  • 80A. Clark.

    Mindware: An Introduction to the Philosophy of Cognitive Science, Oxford University Press, 2001.
  • 81D. Cohn, Z. Ghahramani, M. Jordan.

    Active learning with statistical models, in: Journal of artificial intelligence research, 1996, vol. 4, pp. 129–145.
  • 82W. Croft, D. Cruse.

    Cognitive Linguistics, Cambridge Textbooks in Linguistics, Cambridge University Press, 2004.
  • 83M. Csikszenthmihalyi.

    Flow-the psychology of optimal experience, Harper Perennial, 1991.
  • 84N. Daddaoua, M. Lopes, J. Gottlieb.

    Intrinsically motivated oculomotor exploration guided by uncertainty reduction and conditioned reinforcement in non-human primates, in: Nature Scientific Reports, 2016.
  • 85P. Dayan, W. Belleine.

    Reward, motivation and reinforcement learning, in: Neuron, 2002, vol. 36, pp. 285–298.
  • 86E. Deci, R. Ryan.

    Intrinsic Motivation and Self-Determination in Human Behavior, Plenum Press, 1985.
  • 87J. Elman.

    Learning and development in neural networks: The importance of starting small, in: Cognition, 1993, vol. 48, pp. 71–99.
  • 88S. 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.
  • 89S. Forestier, P.-Y. Oudeyer.

    Towards hierarchical curiosity-driven exploration of sensorimotor models, in: Development and Learning and Epigenetic Robotics (ICDL-EpiRob), 2015 Joint IEEE International Conference on, Aug 2015, pp. 234-235. [ DOI : 10.1109/DEVLRN.2015.7346146 ]
  • 90J. 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, no 11, pp. 585–593.
  • 91J. Grizou.

    Learning from Unlabeled Interaction Frames, Université de Bordeaux, October 2014.

    https://hal.inria.fr/tel-01095562
  • 92J. 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
  • 93S. Harnad.

    The symbol grounding problem, in: Physica D, 1990, vol. 40, pp. 335–346.
  • 94M. Hasenjager, H. Ritter.

    Active learning in neural networks, Physica-Verlag GmbH, Heidelberg, Germany, Germany, 2002, pp. 137–169.
  • 95J. Haugeland.

    Artificial Intelligence: the very idea, The MIT Press, Cambridge, MA, USA, 1985.
  • 96J.-C. Horvitz.

    Mesolimbocortical and nigrostriatal dopamine responses to salient non-reward events, in: Neuroscience, 2000, vol. 96, no 4, pp. 651-656.
  • 97X. 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.
  • 98S. 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
  • 99M. Johnson.

    Developmental Cognitive Neuroscience, 2nd, Blackwell publishing, 2005.
  • 100C. Kidd, B. Hayden.

    The psychology and neuroscience of curiosity, in: Neuron (in press), 2015.
  • 101W. 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.
  • 102M. 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
  • 103G. Loewenstein.

    The psychology of curiosity: A review and reinterpretation., in: Psychological bulletin, 1994, vol. 116, no 1, 75 p.
  • 104M. 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
  • 105M. 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
  • 106M. Lungarella, G. Metta, R. Pfeifer, G. Sandini.

    Developmental Robotics: A Survey, in: Connection Science, 2003, vol. 15, no 4, pp. 151-190.
  • 107N. Lyubova, D. Filliat.

    Developmental Approach for Interactive Object Discovery, in: Neural Networks (IJCNN), The 2012 International Joint Conference on, Australia, 2012, pp. 1-7.

    http://hal.inria.fr/hal-00755298
  • 108J. 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.
  • 109M. 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
  • 110B. Miard, P. Rouanet, J. Grizou, M. Lopes, J. Gottlieb, A. Baranes, P.-Y. Oudeyer.

    A new experimental setup to study the structure of curiosity-driven exploration in humans, in: ICDL-EPIROB 2014, Genoa, Italy, October 2014.

    https://hal.inria.fr/hal-01061682
  • 111P. Miller.

    Theories of developmental psychology, 4th, New York: Worth, 2001.
  • 112M. Mirolli, G. Baldassarre.

    Functions and mechanisms of intrinsic motivations, in: Intrinsically Motivated Learning in Natural and Artificial Systems, Springer, 2013, pp. 49–72.
  • 113C. 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, no 1006. [ DOI : 10.3389/fpsyg.2013.01006 ]

    https://hal.inria.fr/hal-00927940
  • 114C. 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
  • 115C. 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
  • 116S. 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
  • 117S. 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
  • 118S. M. Nguyen, P.-Y. Oudeyer.

    Active Choice of Teachers, Learning Strategies and Goals for a Socially Guided Intrinsic Motivation Learner, in: Paladyn Journal of Bejavioral Robotics, September 2012, vol. 3, no 3, pp. 136-146. [ DOI : 10.2478/s13230-013-0110-z ]

    http://hal.inria.fr/hal-00936932
  • 119P.-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
  • 120P.-Y. Oudeyer, F. Kaplan, V. Hafner.

    Intrinsic Motivation for Autonomous Mental Development, in: IEEE Transactions on Evolutionary Computation, January 2007, vol. 11, no 2, pp. 265-286. [ DOI : 10.1109/TEVC.2006.890271 ]

    https://hal.inria.fr/hal-00793610
  • 121P.-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.
  • 122P.-Y. Oudeyer, F. Kaplan.

    What is intrinsic motivation? A typology of computational approaches, in: Frontiers in Neurorobotics, 2007, vol. 1, no 1.
  • 123P.-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/
  • 124P.-Y. Oudeyer.

    Developmental Learning of Sensorimotor Models for Control in Robotics, in: SIAM News, September 2014, vol. 47, no 7.

    https://hal.inria.fr/hal-01061633
  • 125P.-Y. Oudeyer, L. Smith.

    How evolution may work through curiosity-driven developmental process, in: Topics Cogn. Sci, 2014.
  • 126P.-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/
  • 127M. 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.
  • 128A. 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.
  • 129E. 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, no 1, pp. 86–90.
  • 130V. G. Santucci, G. Baldassarre, M. Mirolli.

    Which is the best intrinsic motivation signal for learning multiple skills?, in: Frontiers in neurorobotics, 2013, vol. 7.
  • 131T. 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/
  • 132M. 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
  • 133J. 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.
  • 134W. Schultz, P. Dayan, P. Montague.

    A neural substrate of prediction and reward, in: Science, 1997, vol. 275, pp. 1593-1599.
  • 135L. Steels.

    Language games for autonomous robots, in: Intelligent Systems, IEEE, 2001, vol. 16, no 5, pp. 16–22.
  • 136E. 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.
  • 137E. Thelen, L. B. Smith.

    A dynamic systems approach to the development of cognition and action, MIT Press, Cambridge, MA, 1994.
  • 138A. 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.
  • 139A. Turing.

    Computing machinery and intelligence, in: Mind, 1950, vol. 59, pp. 433-460.
  • 140M. 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.
  • 141F. Varela, E. Thompson, E. Rosch.

    The embodied mind : Cognitive science and human experience, MIT Press, Cambridge, MA, 1991.
  • 142J. 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.


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