A. Barto, S. Singh, and N. Chentanez, Intrinsically motivated learning of hierarchical collections of skills, Proceedings of ICDL, 2004.

B. Biguer, M. Jeannerod, and C. Prablanc, The coordination of eye, head, and arm movements during reaching at a single visual target, Experimental Brain Research, vol.41, issue.2, pp.301-304, 1982.
DOI : 10.1007/BF00237188

J. Bongard, V. Zykov, and H. Lipson, Resilient Machines Through Continuous Self-Modeling, Science, vol.314, issue.5802, pp.3141118-1121, 2006.
DOI : 10.1126/science.1133687

J. Clune, K. Stanley, R. Pennock, and C. Ofria, On the Performance of Indirect Encoding Across the Continuum of Regularity, IEEE Transactions on Evolutionary Computation, vol.15, issue.3, pp.346-367, 2011.
DOI : 10.1109/TEVC.2010.2104157

K. Currie and A. Tate, O-Plan: The open planning architecture, Artificial Intelligence, vol.52, issue.1, pp.49-86, 1991.
DOI : 10.1016/0004-3702(91)90024-E

T. Dean and M. Wellman, Planning and control, 1991.

K. Deb, A. Pratap, S. Agarwal, and T. Meyarivan, A fast and elitist multiobjective genetic algorithm: NSGA-II, IEEE Transactions on Evolutionary Computation, vol.6, issue.2, pp.182-197, 2002.
DOI : 10.1109/4235.996017

M. Graziano, THE ORGANIZATION OF BEHAVIORAL REPERTOIRE IN MOTOR CORTEX, Annual Review of Neuroscience, vol.29, issue.1, pp.105-139, 2006.
DOI : 10.1146/annurev.neuro.29.051605.112924

G. Hornby, S. Takamura, T. Yamamoto, and M. Fujita, Autonomous evolution of dynamic gaits with two quadruped robots, IEEE Transactions on Robotics, vol.21, issue.3, pp.402-410, 2005.
DOI : 10.1109/TRO.2004.839222

R. Jacobs, M. Jordan, S. Nowlan, and G. Hinton, Adaptive Mixtures of Local Experts, Neural Computation, vol.4, issue.1, pp.79-87, 1991.
DOI : 10.1162/neco.1989.1.2.281

H. Kimura, T. Yamashita, and S. Kobayashi, Reinforcement learning of walking behavior for a four-legged robot, Proceedings of the 40th IEEE Conference on Decision and Control (Cat. No.01CH37228), pp.411-416, 2001.
DOI : 10.1109/CDC.2001.980135

J. Knowles and D. Corne, Quantifying the Effects of Objective Space Dimension in Evolutionary Multiobjective Optimization, Evolutionary Multi-Criterion Optimization, pp.757-771
DOI : 10.1007/978-3-540-70928-2_57

J. Kodjabachian and J. Meyer, Evolution and development of neural controllers for locomotion, gradient-following, and obstacle-avoidance in artificial insects, IEEE Transactions on Neural Networks, vol.9, issue.5, pp.796-812, 1998.
DOI : 10.1109/72.712153
URL : https://hal.archives-ouvertes.fr/hal-01184992

N. Kohl and P. Stone, Policy gradient reinforcement learning for fast quadrupedal locomotion, IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004, pp.2619-2624, 2004.
DOI : 10.1109/ROBOT.2004.1307456
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.5.685

S. Koos, J. Mouret, and S. Doncieux, The Transferability Approach: Crossing the Reality Gap in Evolutionary Robotics, IEEE Transactions on Evolutionary Computation, vol.17, issue.1, pp.122-145, 2013.
DOI : 10.1109/TEVC.2012.2185849
URL : https://hal.archives-ouvertes.fr/hal-00687617

J. Lehman and K. Stanley, Abandoning Objectives: Evolution Through the Search for Novelty Alone, Evolutionary Computation, vol.7, issue.3, pp.189-223, 2011.
DOI : 10.1016/0165-6074(93)90215-7

J. Lehman and K. Stanley, Evolving a diversity of virtual creatures through novelty search and local competition, Proceedings of the 13th annual conference on Genetic and evolutionary computation, GECCO '11, pp.211-218, 2011.
DOI : 10.1145/2001576.2001606

S. Mahdavi and P. Bentley, Innately adaptive robotics through embodied evolution, Autonomous Robots, vol.7, issue.4, pp.149-163, 2006.
DOI : 10.1007/s10514-006-5941-6
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.157.4112

J. Mouret and S. Doncieux, Sferesv2: Evolvin' in the Multi-Core World, Proceedings of IEEE CEC, pp.4079-4086, 2010.
URL : https://hal.archives-ouvertes.fr/hal-00687633

J. Mouret, S. Doncieux, and J. Meyer, Incremental evolution of target-following neuro-controllers for flapping-wing animats. From Animals to Animats 9, 2006.
URL : https://hal.archives-ouvertes.fr/hal-01300724

P. Oudeyer, Intelligent adaptive curiosity: a source of self-development, Proceedings of the Fourth International Workshop on Epigenetic Robotics, pp.127-130, 2004.

S. Russell, P. Norvig, and E. Davis, Artificial intelligence: a modern approach, 2010.

G. Seber, Multivariate observations, 1984.
DOI : 10.1002/9780470316641

R. Tedrake, T. Zhang, and H. Seung, Learning to walk in 20 minutes, Proceedings of Yale workshop on Adaptive and Learning Systems, 2005.

A. A. Algorithm and . Parameters, moin.wsgi/ BehavioralRepertoireLearningInRobotics BR-Evolution experiments: ? Population size: 100 individuals ? Number of generation: 10 000 ? Mutation rate: 10% on each parameters ? Crossover: disabled ? ?: 0.10 m ? ? variation: none Control experiments: ? Population size : 100 individuals ? Number of generation, * 500) ? Mutation rate : 10% on each parameters ? Crossover : disable, pp.50-50