C. Blakemore and G. F. Cooper, Development of the brain depends on the visual environment, Nature, vol.228, pp.477-478, 1970.

J. Bongard, V. Zykov, and H. Lipson, Resilient machines through continuous self-modeling, Science, vol.314, pp.1118-1121, 2006.

S. Ganguli and H. Sompolinsky, Compressed sensing, sparsity, and dimensionality in neuronal information processing and data analysis, Annu. Rev. Neurosci, vol.35, pp.485-508, 2012.

A. Gloye, F. Wiesel, O. Tenchio, and M. Simon, Reinforcing the driving quality of soccer playing robots by anticipation, Inf. Technol, vol.47, pp.250-257, 2005.

G. Gordon, A. , and E. , Reinforcement active learning hierarchical loops, The 2011 International Joint Conference on, pp.3008-3015, 2011.

R. Held and A. Hein, Movement-produced stimulation in the development of visually guided behavior, J. Comp. Physiol. Psychol, vol.56, pp.872-876, 1963.

M. Hersch, E. L. Sauser, and A. Billard, Online learning of the body schema, Int. J. HR, vol.5, pp.161-181, 2008.

M. Hoffmann, H. G. Marques, A. Hernandez-arieta, H. Sumioka, M. Lungarella et al., Body schema in robotics: a review, IEEE Trans. Auton. Ment. Dev, vol.2, pp.304-324, 2010.

F. Kaplan and P. Oudeyer, Maximizing learning progress: an internal reward system for development, Embodied Artificial Intelligence, pp.259-270, 2004.

A. S. Klyubin, D. Polani, and C. L. Nehaniv, Empowerment: a universal agent-centric measure of control, Evolutionary Computation, 2005. The, vol.1, pp.128-135, 2005.

E. S. Klyubin, D. Polani, and C. L. Nehaniv, Tracking information flow through the environment: simple cases of stigmergy, Artificial Life IX: Proceedings of the Ninth International Conference on the Simulation and Synthesis of Living Systems, pp.563-568, 2004.

S. Koos, A. Cully, and J. Mouret, Fast damage recovery in robotics with the t-resilience algorithm, Int. J. Rob. Res, vol.32, pp.1700-1723, 2013.
URL : https://hal.archives-ouvertes.fr/hal-00932862

B. Kuipers, Modeling spatial knowledge, Cogn. Sci, vol.2, pp.129-153, 1978.

A. Laflaquiere, S. Argentieri, O. Breysse, S. Genet, and B. Gas, A nonlinear approach to space dimension perception by a naive agent, Intelligent Robots and Systems (IROS), pp.3253-3259, 2012.

D. M. Mackay, Aspects of the theory of artificial intelligence, The Proceedings of the First International Symposium on Biosimulation Locarno, pp.83-104, 1960.

H. Markram, W. Gerstner, and P. J. Sjöström, A history of spike-timingdependent plasticity, Front. Syn. Neurosci, vol.3, p.4, 2011.

J. Nicod, The Foundations of Geometry and Induction, 1929.

J. K. O'regan and A. Noë, A sensorimotor account of vision and visual consciousness, Behav. Brain. Sci, vol.24, pp.939-972, 2001.

D. Philipona, J. O'regan, and J. Nadal, Is there something out there? inferring space from sensorimotor dependencies, Neural Comput, vol.15, pp.2029-2049, 2003.
URL : https://hal.archives-ouvertes.fr/hal-00143855

D. Pierce and B. J. Kuipers, Map learning with uninterpreted sensors and effectors, Artif. Intell, vol.92, pp.169-227, 1997.

H. Poincaré, Science and Hypothesis, 1905.

V. Y. Roschin, A. A. Frolov, Y. Burnod, and M. A. Maier, A neural network model for the acquisition of a spatial body scheme through sensorimotor interaction, Neural Comput, vol.23, pp.1821-1834, 2011.

O. Sigaud, C. Salaün, and V. Padois, On-line regression algorithms for learning mechanical models of robots: a survey, Rob. Auton. Syst, vol.59, pp.1115-1129, 2011.
URL : https://hal.archives-ouvertes.fr/hal-00629133

A. V. Terekhov and J. K. Regan, Learning abstract perceptual notions: the example of space, Development and Learning and Epigenetic Robotics (ICDL-Epirob), pp.368-373, 2014.

J. Von-uexküll, A stroll through the worlds of animals and men: a picture book of invisible worlds, Instinctive Behavior: The Development of a Modern Concept, pp.5-80, 1957.

L. Zhaoping, Theoretical understanding of the early visual processes by data compression and data selection, Network, vol.17, pp.301-334, 2006.