J. Weng, J. Mcclelland, A. Pentland, and O. , ARTIFICIAL INTELLIGENCE: Autonomous Mental Development by Robots and Animals, Science, vol.291, issue.5504, pp.599-600, 2001.
DOI : 10.1126/science.291.5504.599

M. Lungarella, G. Metta, R. Pfeifer, and G. Sandini, Developmental robotics: a survey, Connection Science, vol.1, issue.4, p.151190, 2003.
DOI : 10.2307/1131322

S. Calinon, F. Guenter, and A. Billard, On Learning, Representing, and Generalizing a Task in a Humanoid Robot, IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics), vol.37, issue.2, pp.286-298, 2007.
DOI : 10.1109/TSMCB.2006.886952

M. Lopes, F. S. Melo, and L. Montesano, Affordance-based imitation learning in robots, 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems, p.10151021, 2007.
DOI : 10.1109/IROS.2007.4399517

P. Abbeel and A. Y. Ng, Apprenticeship learning via inverse reinforcement learning, Twenty-first international conference on Machine learning , ICML '04, 2004.
DOI : 10.1145/1015330.1015430

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.2.92

C. G. Atkeson and S. Schaal, Robot learning from demonstration, Proc. 14th International Conference on Machine Learning, p.1220, 1997.

A. Alissandrakis, C. L. Nehaniv, and K. Dautenhahn, Action, State and Effect Metrics for Robot Imitation, ROMAN 2006, The 15th IEEE International Symposium on Robot and Human Interactive Communication, p.232237, 2006.
DOI : 10.1109/ROMAN.2006.314423

B. Argall, S. Chernova, and M. Veloso, A survey of robot learning from demonstration, Robotics and Autonomous Systems, vol.57, issue.5, p.469483, 2009.
DOI : 10.1016/j.robot.2008.10.024

M. Asada, M. Ogino, S. Matsuyama, and J. Oga, Imitation Learning Based on Visuo-Somatic Mapping
DOI : 10.1007/11552246_26

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.330.3264

P. Andry, P. Gaussier, S. Moga, J. P. Banquet, and J. Nadel, Learning and communication via imitation: an autonomous robot perspective, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans, vol.31, issue.5, pp.31-431, 2001.
DOI : 10.1109/3468.952717

Y. Demiris and A. Meltzoff, The Robot in the Crib: A developmental , Infant and Child Development, pp.43-53, 2008.

M. Pardowitz, S. Knoop, R. D. Zollner, and R. Dillmann, Incremental Learning of Tasks From User Demonstrations, Past Experiences, and Vocal Comments, IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics), vol.37, issue.2, p.322332, 2007.
DOI : 10.1109/TSMCB.2006.886951

E. Oztop, M. Kawato, and M. Arbib, Mirror neurons and imitation: A computationally guided review, Neural Networks, vol.19, issue.3, p.254271, 2006.
DOI : 10.1016/j.neunet.2006.02.002

R. Rao, A. Shon, and A. Meltzoff, Imitation and social learning in robots, humans, and animals, chap. A Bayesian model of imitation in infants and robots, 2007.

R. C. Arkin, Moving Up the Food Chain, 2005.
DOI : 10.1093/acprof:oso/9780195166194.003.0009

J. M. Fellous and M. Arbib, Who Needs Emotions: The Brain Meets the Robot, 2005.
DOI : 10.1093/acprof:oso/9780195166194.001.0001

D. Mcfarland and T. Bosser, Intelligent Behavior in Animals and Robots, 1993.

R. Manzotti and V. Tagliasco, From behaviour-based robots to motivation-based robots, Robotics and Autonomous Systems, vol.51, issue.2-3, pp.175-190, 2005.
DOI : 10.1016/j.robot.2004.10.004

A. Stoytchev and R. Arkin, Incorporating Motivation in a Hybrid Robot Architecture, JACIII, vol.8, issue.3, pp.269-274, 2004.

R. C. Arkin, M. Fujita, T. Takagi, and R. Hasegawa, An ethological and emotional basis for human???robot interaction, Robotics and Autonomous Systems, vol.42, issue.3-4, pp.191-201, 2003.
DOI : 10.1016/S0921-8890(02)00375-5

R. White, Motivation reconsidered: The concept of competence. Psychological, Curiosity and Exploration, Science, vol.66, issue.153 3731, pp.297333-297358, 1959.

E. Deci and R. Ryan, Intrinsic Motivation and Self-Determination in Human Behavior, 1985.
DOI : 10.1007/978-1-4899-2271-7

W. Schultz, Getting Formal with Dopamine and Reward, Neuron, vol.36, issue.2, pp.241-263, 2002.
DOI : 10.1016/S0896-6273(02)00967-4

URL : http://doi.org/10.1016/s0896-6273(02)00967-4

P. Dayan and B. Balleine, Reward, Motivation, and Reinforcement Learning, Neuron, vol.36, issue.2, pp.285-298, 2002.
DOI : 10.1016/S0896-6273(02)00963-7

P. Redgrave and K. Gurney, The short-latency dopamine signal: a role in discovering novel actions?, Nature Reviews Neuroscience, vol.9, issue.4, pp.967-975, 2006.
DOI : 10.1038/nrn2022

P. Oudeyer, F. Kaplan, and V. Hafner, Intrinsic Motivation Systems for Autonomous Mental Development, IEEE Transactions on Evolutionary Computation, vol.11, issue.2, p.265286, 2007.
DOI : 10.1109/TEVC.2006.890271

A. Barto, S. Singh, and N. Chentanez, Intrinsically motivated learning of hierarchical collections of skills, Proc. 3rd Int. Conf. Development Learn, p.112119, 2004.

A. Blanchard and L. Cañamero, Modulation of Exploratory Behavior for Adaptation to the Context. Biologically Inspired Robotics (Biro-net) : Adaptation in Artificial and Biological Systems, 2006.

R. Der, M. Herrmann, R. Liebscher-dillman, R. Schraft, R. D. W¨orn et al., Homeokinetic approach to autonomous learning in mobile robots, In Robotik, pp.301-306, 2002.

D. S. Blank, D. Kumar, L. Meeden, and J. Marshall, BRINGING UP ROBOT: FUNDAMENTAL MECHANISMS FOR CREATING A SELF-MOTIVATED, SELF-ORGANIZING ARCHITECTURE, Cybernetics and Systems, vol.36, issue.2, 2005.
DOI : 10.1126/science.291.5504.599

X. Huang and J. Weng, Novelty and Reinforcement Learning in the Value System of Developmental Robots, Proc. Second International Workshop on Epigenetic Robotics: Modeling Cognitive Development in Robotic Systems, 2002.

J. Schmidhuber, Curious model-building control systems, [Proceedings] 1991 IEEE International Joint Conference on Neural Networks, p.14581463, 1991.
DOI : 10.1109/IJCNN.1991.170605

M. Schembri, M. Mirolli, and G. Baldassarre, Evolution and Learning in an Intrinsically Motivated Reinforcement Learning Robot, ECAL, vol.2007, pp.294-303, 2007.
DOI : 10.1007/978-3-540-74913-4_30

V. Fedorov, Theory of Optimal Experiment, Academic, 1972.

E. J. Gibson, Principles of Perceptual Learning and Development, Leonardo, vol.6, issue.2, 1969.
DOI : 10.2307/1572721

M. Csikszentmihalyi, Creativity-Flow and the Psychology of Discovery and Invention, 1996.

D. Cohn, Z. Ghahramani, and M. Jordan, Active learning with statistical models, J. Artif. Intell. Res, vol.4, p.129145, 1996.

M. Hasenjager and H. Ritter, Active Learning in Neural Networks, p.137169, 2002.
DOI : 10.1007/978-3-7908-1803-1_5

S. Vijayakumar and S. Schaal, LWPR : An O(n) Algorithm for Incremental Real Time Learning in High Dimensional Space, Proc. of Seventeenth International Conference on Machine Learning (ICML2000) Stanford, California, pp.1079-1086, 2000.

A. D. Souza, S. Vijayakumar, and S. Schaal, Learning inverse kinematics, IEEE International Conference on Intelligent Robots and Systems, 2001.

J. Peters and S. Schaal, Learning to Control in Operational Space, The International Journal of Robotics Research, vol.12, issue.12, pp.197-212, 2008.
DOI : 10.1177/0278364907087548

C. Salaün, V. Padois, and O. Sigaud, Control of redundant robots using learned models: An operational space control approach, 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2009.
DOI : 10.1109/IROS.2009.5354438

D. Y. Yeung and Y. Zhang, Learning inverse dynamics by Gaussian process regression under the multi-task learning framework, The

A. Baranes and P. Oudeyer, R-IAC: Robust Intrinsically Motivated Exploration and Active Learning, IEEE Transactions on Autonomous Mental Development, vol.1, issue.3, pp.155-169, 2009.
DOI : 10.1109/TAMD.2009.2037513

URL : https://hal.archives-ouvertes.fr/hal-00818174

Z. Ghahramani, Solving inverse problems using an EM approach to density estimation

C. E. Rasmussen, on of Gaussian Process and other Methods for Non, 1996.

S. Arya, D. M. Mount, N. S. Netanyahu, R. Silverman, and A. Y. Wu, An optimal algorithm for approximate nearest neighbor searching fixed dimensions, Journal of the ACM, vol.45, issue.6, pp.891-923, 1998.
DOI : 10.1145/293347.293348

S. Maneewongvatana and D. M. Mount, Analysis of Approximate Nearest Neighbor Searching with Clustered Point Sets, Data Structures, Near Neighbor Searches, and Methodology: Fifth and Sixth DIMACS Implementation Challenges, the DIMACS Series in Discr. Math. and Theoret

D. Filliat, A visual bag of words method for interactive qualitative localization and mapping, Proceedings 2007 IEEE International Conference on Robotics and Automation, 2007.
DOI : 10.1109/ROBOT.2007.364080

URL : https://hal.archives-ouvertes.fr/hal-00640996

P. Oudeyer and F. Kaplan, How can we define intrinsic motivation?, Proceedings of the 8th International Conference on Epigenetic Robotics: Modeling Cognitive Development in Robotic Systems, 2008.
URL : https://hal.archives-ouvertes.fr/inria-00420175

Y. Kuniyoshi, Y. Yorozu, M. Inaba, and H. Inoue, From visuo-motor self learning to early imitation-a neural architecture for humanoid learning, 2003 IEEE International Conference on Robotics and Automation (Cat. No.03CH37422), p.31323139, 2003.
DOI : 10.1109/ROBOT.2003.1242072

M. Lopes, F. Mello, L. Montesano, and J. , Santos-Victor (to appear) Cognitive processes in imitation : overview and computational approaches, in From motor to interaction learning in robots

A. L. Thomaz and C. Breazeal, Experiments in socially guided exploration: lessons learned in building robots that learn with and without human teachers, Connection Science, vol.1, issue.2-3, pp.91-110, 2008.
DOI : 10.1016/j.artint.2007.09.009

D. Koch, A. Billard-nguyen-tuong, D. , and J. Peters, Gaussian Mixture Regression and its Applicatio Local Gaussian Processes Regression for Real-time Model-based Robot Control Proceedings of the [62] process regression under the multi-In The Path to Autonomous Robots, IEEERSJ International Conference on Intelligent Robots and Systems IEEE Service Center, vol.61, pp.380-385131, 2008.

C. Chang and C. Lin, LIBSVM, ACM Transactions on Intelligent Systems and Technology, vol.2, issue.3, 2001.
DOI : 10.1145/1961189.1961199