EN FR
EN FR


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, p. 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, p. 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, p. 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, p. 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, p. 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, p. 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/
  • 10M. 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
  • 11M. Lopes, F. Melo, L. Montesano.

    Active learning for reward estimation in inverse reinforcement learning, in: Machine Learning and Knowledge Discovery in Databases, 2009, p. 31–46.
  • 12L. 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, p. 15–26.
  • 13S. 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
  • 14P.-Y. Oudeyer, F. Kaplan, V. Hafner.

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

    http://www.pyoudeyer.com/ims.pdf
  • 15P.-Y. Oudeyer.

    Self-Organization in the Evolution of Speech, Studies in the Evolution of Language, Oxford University Press, 2006.
  • 16P.-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, p. 2–16.

    http://hal.inria.fr/inria-00541783/en/
  • 17P. 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
  • 18F. 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.
  • 19F. 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, p. 1–42.
  • 20F. 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, p. 1360-1370.
Publications of the year

Doctoral Dissertations and Habilitation Theses

  • 21P. Rouanet.

    Apprendre à un robot à reconnaître des objets visuels nouveaux et à les associer à des mots nouveaux : le rôle de l'interface, Université Sciences et Technologies - Bordeaux I, April 2012.

    http://hal.inria.fr/tel-00758249

Articles in International Peer-Reviewed Journals

  • 22A. 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, p. 49 - 73. [ DOI : 10.1016/j.robot.2012.05.008 ]

    http://www.pyoudeyer.com/RAS-SAGG-RIAC-2012.pdf
  • 23A. Gepperth, B. Dittes, M. Garcia Ortiz.

    The contribution of context information: a case study of object recognition in an intelligent car, in: Neurocomputing, February 2012, vol. 94. [ DOI : 10.1016/j.neucom.2012.03.008 ]

    http://hal.inria.fr/hal-00763650
  • 24A. 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
  • 25C. Moulin-Frier, R. Laurent, P. Bessière, J.-L. Schwartz, J. Diard.

    Adverse conditions improve distinguishability of auditory, motor and percep-tuo-motor theories of speech perception: an exploratory Bayesian modeling study, in: Language and Cognitive Processes, 2012, vol. 27, no 7-8 Special Issue: Speech Recognition in Adverse Conditions, p. 1240-1263. [ DOI : 10.1080/01690965.2011.645313 ]

    http://hal.archives-ouvertes.fr/hal-00642311
  • 26P. Pastor, M. Kalakrishnan, F. Meier, F. Stulp, J. Buchli, E. Theodorou, S. Schaal.

    From Dynamic Movement Primitives to Associative Skill Memories, in: Robotics and Autonomous Systems, 2012.
  • 27P. Pilarski, M. Dawson, T. Degris, J. Carey, K. Chan, J. Hebert, R. Sutton.

    Prediction and Anticipation for Adaptive Artificial Limbs, in: IEEE Robotics and Automation Magazine. Special Issue on Assistive Robotics, 2013.
  • 28P. 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
  • 29F. 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.
  • 30F. 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, p. 1–42.
  • 31F. 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, p. 1360-1370.

International Conferences with Proceedings

  • 32M. Cakmak, M. Lopes.

    Algorithmic and Human Teaching of Sequential Decision Tasks, in: AAAI Conference on Artificial Intelligence (AAAI-12), Toronto, Canada, July 2012.

    http://hal.inria.fr/hal-00755253
  • 33A. Chapoulie, P. Rives, D. Filliat.

    Topological segmentation of indoors/outdoors sequences of spherical views, in: IEEE Conference on Intelligent Robots and Systems, IROS'12, Vilamoura, Portugal, October 2012, p. 4288-4295.

    http://hal.inria.fr/hal-00752909
  • 34A. Csapo, E. Gilmartin, J. Grizou, J. Han, R. Meena, D. Anastasiou, K. Jokinen, G. Wilcock.

    Multimodal Conversational Interaction with a Humanoid Robot, in: CogInfoCom 2012 (3rd IEEE International Conference on Cognitive Infocommunications), Kosice, Slovakia, December 2012.

    http://hal.inria.fr/hal-00759810
  • 35T. Degris, J. Modayil.

    Scaling-up Knowledge for a Cognizant Robot, in: AAAI Spring Symposium on Designing Intelligent Robots: Reintegrating AI., Stanford, United States, March 2012.

    http://hal.inria.fr/hal-00764289
  • 36N. Degris, P. Pilarski, R. Sutton.

    Apprentissage par Renforcement sans Modèle et avec Action Continue, in: Journées Francophones sur la planification, la décision et l'apprentissage pour le contrôle des systèmes - JFPDA 2012, Villers-lès-Nancy, France, O. Buffet (editor), 2012, 11 p p.

    http://hal.inria.fr/hal-00736314
  • 37T. Degris, P. Pilarski, R. Sutton.

    Model-Free Reinforcement Learning with Continuous Action in Practice, in: American Control Conference, Montreal, Canada, June 2012.

    http://hal.inria.fr/hal-00764281
  • 38T. Degris, M. White, R. Sutton.

    Off-Policy Actor-Critic, in: International Conference on Machine Learning, Edinburgh, United Kingdom, June 2012.

    http://hal.inria.fr/hal-00764021
  • 39D. Filliat, E. Battesti, S. Bazeille, G. Duceux, A. Gepperth, L. Harrath, I. Jebari, R. Pereira, A. Tapus, C. Meyer, S.-H. Ieng, R. Benosman, E. Cizeron, J.-C. Mamanna, B. Pothier.

    RGBD object recognition and visual texture classification for indoor semantic mapping, in: Technologies for Practical Robot Applications (TePRA), 2012 IEEE International Conference on, United States, 2012, p. 127 - 132.

    http://hal.inria.fr/hal-00755295
  • 40A. Gepperth, L.-C. Caron.

    Simultaneous concept formation driven by predictability, in: International conference on development and learning, San Diego, États-Unis, October 2012.
  • 41A. Gepperth.

    Co-training of context models for real-time object detection, in: IEEE Symposium on Intelligent Vehicles, Madrid, Espagne, June 2012.

    http://hal.inria.fr/hal-00763676
  • 42T. Hester, M. Lopes, P. Stone.

    Learning Exploration Strategies in Model-Based Reinforcement Learning, in: AAMAS, 2013.
  • 43S. 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, page : to appear.

    http://hal.inria.fr/hal-00755297
  • 44J. Kulick, M. Toussaint, T. Lang, M. Lopes.

    Active Learning for Teaching a Robot Grounded Relational Symbols, in: ICRA, 2013, submitted.
  • 45C. Lopera, H. Tomé, A. R. Tsouroukdissian, F. Stulp.

    Comparing Motion Generation and Motion Recall for Everyday Robotic Tasks, in: 12th IEEE-RAS International Conference on Humanoid Robots, 2012.
  • 46M. 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
  • 47M. 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.

    http://hal.inria.fr/hal-00755216
  • 48N. Lyubova, D. Filliat.

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

    http://hal.inria.fr/hal-00755298
  • 49N. Lyubova, D. Filliat.

    Developmental Learning for Object Perception, in: Proceedings of the CogSys2012 Workshop on Deep Hierarchies in Vision, Autriche, 2012.

    http://hal.archives-ouvertes.fr/hal-00755300
  • 50A. Mahmood, R. Sutton, T. Degris, P. Pilarski.

    Tuning-Free Step-Size Adaptation, in: Proceedings of the 37th IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2012, p. 2121–2124.
  • 51O. Mangin, P.-Y. Oudeyer.

    Learning the Combinatorial Structure of Demonstrated Behaviors with Inverse Feedback Control, in: Human Behavior Understanding, Springer, October 2012, vol. 7559, Lecture notes in computer science.

    http://hal.inria.fr/hal-00764448
  • 52O. Mangin, P.-Y. Oudeyer.

    Learning to recognize parallel combinations of human motion primitives with linguistic descriptions using non-negative matrix factorization, in: Proceedings of 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems, IEEE, October 2012.

    http://hal.inria.fr/hal-00764353
  • 54S. M. Nguyen, P.-Y. Oudeyer.

    Interactive Learning Gives the Tempo to an Intrinsically Motivated Robot Learner, in: IEEE-RAS International Conference on Humanoid Robots, Osaka, Japan, December 2012.

    http://hal.inria.fr/hal-00762753
  • 55S. M. Nguyen, P.-Y. Oudeyer.

    Properties for Efficient Demonstrations to a Socially Guided Intrinsically Motivated Learner, in: 21st IEEE International Symposium on Robot and Human Interactive Communication, Paris, France, September 2012.

    http://hal.inria.fr/hal-00762758
  • 56S. M. Nguyen, P.-Y. Oudeyer.

    Whom Will an Intrinsically Motivated Robot Learner Choose to Imitate from?, in: Post-Graduate Conference on Robotics and Development of Cognition: RobotDoC-PhD 2012, Lausanne, Switzerland, September 2012.

    http://hal.inria.fr/hal-00762762
  • 57P. Pilarski, M. Dawson, T. Degris, J. Carey, R. Sutton.

    Dynamic switching and real-time machine learning for improved human control of assistive biomedical robots, in: Proceedings of the International Conference on Biomedical Robotics and Biomechatronics (BioRob), 4th IEEE RAS EMBS, 2012, p. 296 -302. [ DOI : 10.1109/BioRob.2012.6290309 ]
  • 58P. Pilarski, T. Degris, M. Dawson, J. Carey, K. Chan, J. Hebert, R. Sutton.

    Towards Prediction-Based Prosthetic Control, in: Proceedings of the 17th International Functional Electrical Stimulation Society Conference (IFESS), 2012.
  • 59A. A. Salah, J. R. del Solar, Ç. Meriçli, P.-Y. Oudeyer.

    Human Behavior Understanding for Robotics., in: Human Behavior Understanding, A. A. Salah, J. R. del Solar, Ç. Meriçli, P.-Y. Oudeyer (editors), Lecture Notes in Computer Science, Springer, 2012, vol. 7559, p. 1-16.
  • 60F. Stulp, P.-Y. Oudeyer.

    Emergent Proximo-Distal Maturation through Adaptive Exploration, in: International Conference on Development and Learning (ICDL), 2012.
  • 61F. Stulp, O. Sigaud.

    Adaptation de la matrice de covariance pour l'apprentissage par renforcement direct, in: Journées Francophones sur la planification, la décision et l'apprentissage pour le contrôle des systèmes - JFPDA 2012, Villers-lès-Nancy, France, O. Buffet (editor), 2012, 12 p p.

    http://hal.inria.fr/hal-00736310
  • 62F. Stulp, O. Sigaud.

    Path Integral Policy Improvement with Covariance Matrix Adaptation, in: Proceedings of the 29th International Conference on Machine Learning (ICML), 2012.
  • 63F. Stulp.

    Adaptive Exploration for Continual Reinforcement Learning, in: International Conference on Intelligent Robots and Systems (IROS), 2012.
  • 64B. Wrede, K. J. Rohlfing, J. J. Steil, S. Wrede, P.-Y. Oudeyer, J. Tani.

    Towards robots with teleological action and language understanding, in: IEEE Humanoids, Workshop on Developmental Robotics, Osaka, IEEE, 2012.

    http://www.pyoudeyer.com/Wredeetal12.pdf

National Conferences with Proceeding

  • 65T. Degris, M. Pilarski, R. Sutton.

    Apprentissage par Renforcement sans Modèle et avec Action Continue, in: 7èmes Journées Francophones Planification, Décision, et Apprentissage pour la conduite de systèmes, Nancy, France, May 2012.

    http://hal.inria.fr/hal-00764325

Scientific Books (or Scientific Book chapters)

  • 66T. Cederborg, P.-Y. Oudeyer.

    Learning words by imitating, in: Theoretical and Computational Models of Word Learning: Trends in Psychology and Artificial Intelligence, L. Gogate, G. Hollich (editors), IGI Global, January 2012.

Books or Proceedings Editing

  • 67A. A. Salah, J. R. del Solar, Ç. Meriçli, P.-Y. Oudeyer.

    A. A. Salah, J. R. del Solar, Ç. Meriçli, P.-Y. Oudeyer (editors), Lecture Notes in Computer Science, Springer, 2012, vol. 7559.

Other Publications

  • 68R. Laurent, C. Moulin-Frier, P. Bessière, J.-L. Schwartz, J. Diard.

    Integrate, yes, but what and how? A computational approach of perceptuo-motor fusion in speech perception., 2012, Accepted commentary in Behavioral and Brain Sciences, in Press..

    http://hal.inria.fr/hal-00765973
  • 69F. Stulp, O. Sigaud.

    Policy Improvement Methods: Between Black-Box Optimization and Episodic Reinforcement Learning, 2012, 34 pages.

    http://hal.inria.fr/hal-00738463
References in notes
  • 70L. Steels, R. Brooks (editors)

    The Artificial Life Route to Artificial Intelligence: Building Embodied, Situated Agents, L. Erlbaum Associates Inc., Hillsdale, NJ, USA, 1995.
  • 71B. Argall, S. Chernova, M. Veloso.

    A Survey of Robot Learning from Demonstration, in: Robotics and Autonomous Systems, 2009, vol. 57, no 5, p. 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, p. 279-303.
  • 73A. 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.
  • 74D. Berlyne.

    Conflict, Arousal and Curiosity, McGraw-Hill, 1960.
  • 75C. Breazeal.

    Designing sociable robots, The MIT Press, 2004.
  • 76R. 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, p. 961–968.
  • 77A. Clark.

    Mindware: An Introduction to the Philosophy of Cognitive Science, Oxford University Press, 2001.
  • 78D. Cohn, Z. Ghahramani, M. Jordan.

    Active learning with statistical models, in: Journal of artificial intelligence research, 1996, vol. 4, p. 129–145.
  • 79W. Croft, D. Cruse.

    Cognitive Linguistics, Cambridge Textbooks in Linguistics, Cambridge University Press, 2004.
  • 80M. Csikszenthmihalyi.

    Flow-the psychology of optimal experience, Harper Perennial, 1991.
  • 81P. Dayan, W. Belleine.

    Reward, motivation and reinforcement learning, in: Neuron, 2002, vol. 36, p. 285–298.
  • 82E. Deci, R. Ryan.

    Intrinsic Motivation and Self-Determination in Human Behavior, Plenum Press, 1985.
  • 83T. Degris, M. White, R. Sutton.

    Off-Policy Actor-Critic, in: arXiv preprint arXiv:1205.4839, 2012.
  • 84J. Elman.

    Learning and development in neural networks: The importance of starting small, in: Cognition, 1993, vol. 48, p. 71–99.
  • 85C. Fleischer, A. Wege, K. Kondak, G. Hommel.

    Application of EMG signals for controlling exoskeleton robots, in: Biomedizinische Technik, 2006, vol. 51, no 5/6, p. 314–319.
  • 86D. Gouaillier, V. Hugel, P. Blazevic, C. Kilner, J. Monceaux, P. Lafourcade, B. Marnier, J. Serre, B. Maisonnier.

    The nao humanoid: a combination of performance and affordability, in: CoRR, vol. abs/0807.3223, 2008.
  • 87I. Ha, Y. Tamura, H. Asama, J. Han, D. Hong.

    Development of open humanoid platform DARwIn-OP, in: SICE Annual Conference (SICE), 2011 Proceedings of, IEEE, 2011, p. 2178–2181.
  • 88S. Harnad.

    The symbol grounding problem, in: Physica D, 1990, vol. 40, p. 335–346.
  • 89M. Hasenjager, H. Ritter.

    Active learning in neural networks, Physica-Verlag GmbH, Heidelberg, Germany, Germany, 2002, p. 137–169.
  • 90J. Haugeland.

    Artificial Intelligence: the very idea, The MIT Press, Cambridge, MA, USA, 1985.
  • 91J.-C. Horvitz.

    Mesolimbocortical and nigrostriatal dopamine responses to salient non-reward events, in: Neuroscience, 2000, vol. 96, no 4, p. 651-656.
  • 92X. 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, p. 47–55.
  • 93M. Johnson.

    Developmental Cognitive Neuroscience, 2nd, Blackwell publishing, 2005.
  • 94W. 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, p. 5–12.
  • 95M. Lapeyre, O. Ly, P. Oudeyer.

    Maturational constraints for motor learning in high-dimensions: the case of biped walking, in: Humanoid Robots (Humanoids), 2011 11th IEEE-RAS International Conference on, IEEE, 2011, p. 707–714.
  • 96M. 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, p. 1 - 7. [ DOI : 10.1109/DEVLRN.2011.6037359 ]

    http://hal.inria.fr/hal-00636166/en
  • 97M. Lungarella, G. Metta, R. Pfeifer, G. Sandini.

    Developmental Robotics: A Survey, in: Connection Science, 2003, vol. 15, no 4, p. 151-190.
  • 98O. Ly, M. Lapeyre, P. Oudeyer.

    Bio-inspired vertebral column, compliance and semi-passive dynamics in a lightweight humanoid robot, in: Intelligent Robots and Systems (IROS), 2011 IEEE/RSJ International Conference on, IEEE, 2011, p. 1465–1472.
  • 99O. Mangin, P.-Y. Oudeyer.

    Unsupervised learning of simultaneous motor primitives through imitation, in: IEEE ICDL-EPIROB 2011, Frankfurt, Germany, August 2011.

    http://hal.inria.fr/hal-00652346/en
  • 100J. 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.
  • 101M. 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
  • 102P. Miller.

    Theories of developmental psychology., 4th, New York: Worth, 2001.
  • 103L. Montesano, M. Lopes.

    Active learning of visual descriptors for grasping using non-parametric smoothed beta distributions, in: Robotics and Autonomous Systems, 2011, p. 26-AUG-2011. [ DOI : 10.1016/j.robot.2011.07.013 ]

    http://hal.inria.fr/hal-00637575/en
  • 104S. 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
  • 105S. 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, Germany, 2011, ERC Grant EXPLORERS 240007.

    http://hal.archives-ouvertes.fr/hal-00645986
  • 106S. 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
  • 107R. Nowak.

    The Geometry of Generalized Binary Search, in: Information Theory, Transactions on, 2011, vol. 57, no 12, p. 7893–7906.
  • 108P.-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, p. 127–130.
  • 109P.-Y. Oudeyer, F. Kaplan.

    What is intrinsic motivation? A typology of computational approaches, in: Frontiers in Neurorobotics, 2007, vol. 1, no 1.
  • 110P.-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/
  • 111P.-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, p. 83-112.

    http://hal.inria.fr/inria-00446908/en/
  • 112A. 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.
  • 113T. 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/
  • 114M. 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, p. 282-287.

    http://dx.doi.org/10.1109/DEVLRN.2007.4354052
  • 115J. Schmidhuber.

    Curious Model-Building Control Systems, in: Proceedings of the International Joint Conference on Neural Networks, Singapore, IEEE press, 1991, vol. 2, p. 1458–1463.
  • 116W. Schultz, P. Dayan, P. Montague.

    A neural substrate of prediction and reward, in: Science, 1997, vol. 275, p. 1593-1599.
  • 117M. Schwarz, M. Schreiber, S. Schueller, M. Missura, S. Behnke.

    NimbRo-OP Humanoid TeenSize Open Platform.
  • 118E. Thelen, L. B. Smith.

    A dynamic systems approach to the development of cognition and action, MIT Press, Cambridge, MA, 1994.
  • 119A. L. Thomaz, C. Breazeal.

    Teachable robots: Understanding human teaching behavior to build more effective robot learners, in: Artificial Intelligence Journal, 2008, vol. 172, p. 716-737.
  • 120A. Turing.

    Computing machinery and intelligence, in: Mind, 1950, vol. 59, p. 433-460.
  • 121F. Varela, E. Thompson, E. Rosch.

    The embodied mind : Cognitive science and human experience, MIT Press, Cambridge, MA, 1991.
  • 122J. 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, p. 599-600.