P. J. Angeline, G. M. Saunders, and J. P. Pollack, An evolutionary algorithm that constructs recurrent neural networks, IEEE Transactions on Neural Networks, vol.5, issue.1, pp.54-65, 1994.
DOI : 10.1109/72.265960

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

A. Auger and N. Hansen, A Restart CMA Evolution Strategy With Increasing Population Size, 2005 IEEE Congress on Evolutionary Computation, pp.1769-1776, 2005.
DOI : 10.1109/CEC.2005.1554902

S. Babinec, Evolutionary optimization methods in echo state networks, 6th Czech-Slovak Workshop on Cognition and Artificial Life, 2006.

W. Banzhaf, On the Dynamics of an Artificial Regulatory Network, pp.217-227, 2003.
DOI : 10.1007/978-3-540-39432-7_24

H. Beyer and H. Schwefel, Evolution strategies, Scholarpedia, vol.2, issue.8, pp.3-52, 2002.
DOI : 10.4249/scholarpedia.1965

D. B. and K. O. Stanley, A novel generative encoding for exploiting neural network sensor and output geometry, p.7, 2007.

G. Dematos, M. Boyd, B. Kermanshahi, N. Kohzadi, and I. Kaastra, Feedforward versus recurrent neural networks for forecasting monthly japanese yen exchange rates, Financial Engineering and the Japanese Markets, vol.12, issue.1, pp.59-75, 1996.
DOI : 10.1007/BF00868008

A. Devert, N. Bredeche, and M. Schoenauer, Robust multi-cellular developmental design, Proceedings of the 9th annual conference on Genetic and evolutionary computation , GECCO '07, 2007.
DOI : 10.1145/1276958.1277156

URL : https://hal.archives-ouvertes.fr/inria-00145336

P. Durr, C. Mattiussi, and D. Floreano, Neuroevolution with Analog Genetic Encoding, PPSN IX, pp.671-680, 2006.
DOI : 10.1007/11844297_68

S. E. Fahlman and C. Lebiere, The cascade-correlation learning architecture, Advances in Neural Information Processing Systems, pp.524-532, 1989.

D. Federici and K. Downing, Evolution and Development of a Multicellular Organism: Scalability, Resilience, and Neutral Complexification, Artificial Life, vol.21, issue.4, pp.381-409, 2006.
DOI : 10.1038/ng1340

F. Gomez and R. Miikkulainen, Incremental Evolution of Complex General Behavior, Adaptive Behavior, vol.5, issue.3-4, 1996.
DOI : 10.1177/105971239700500305

T. G. Gordon and P. J. Bentley, Bias and scalability in evolutionary development, Proceedings of the 2005 conference on Genetic and evolutionary computation , GECCO '05, pp.83-90, 2005.
DOI : 10.1145/1068009.1068021

F. Gruau, Genetic synthesis of modular neural networks, ICGA-93, pp.318-325, 1993.

P. Husbands, T. Smith, M. O. Jakobi, and . Shea, Better Living Through Chemistry: Evolving GasNets for Robot Control, Connection Science, vol.10, issue.3-4, pp.3-4185, 1998.
DOI : 10.1080/095400998116404

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

H. Jaeger, The Echo State approach to analysing and training recurrent neural networks, 2001.

H. Jaeger, Tutorial on training recurrent neural networks, 2002.

S. Kern, S. D. Müller, N. Hansen, D. Büche, J. Ocenasek et al., Learning probability distributions in continuous evolutionary algorithms ??? a comparative review, Natural Computing, vol.3, issue.1, pp.77-112, 2004.
DOI : 10.1023/B:NACO.0000023416.59689.4e

T. Kohonen, Self-Organizing Maps, volume 30 of Springer Series in Information Sciences, 1995.

Y. Lecun, Learning processes in an asymmetric threshold network, Disordered systems and biological organization, pp.233-240, 1986.

Y. Lecun, B. Boser, J. S. Denker, D. Henderson, R. E. Howard et al., Backpropagation Applied to Handwritten Zip Code Recognition, Neural Computation, vol.1, issue.4, pp.541-551, 1989.
DOI : 10.1007/BF00133697

Y. Lecun, J. S. Denker, S. Solla, R. E. Howard, and L. D. , Optimal brain damage, 1990.

J. F. Miller, Evolving a Self-Repairing, Self-Regulating, French Flag Organism, GECCO, pp.129-139, 2004.
DOI : 10.1007/978-3-540-24854-5_12

D. E. Moriarty, Symbiotic evolution of neural networks in sequential decision tasks, 1997.

M. C. Ozturk, D. Xu, and J. C. Principe, Analysis and Design of Echo State Networks, Neural Computation, vol.7, issue.1, pp.111-138, 2007.
DOI : 10.1162/neco.1989.1.2.270

B. A. Pearlmutter, Gradient calculations for dynamic recurrent neural networks: a survey, IEEE Transactions on Neural Networks, vol.6, issue.5, pp.1212-1228, 1995.
DOI : 10.1109/72.410363

I. Rechenberg, Evolutionsstrategie: Optimierung technischer Systeme nach Prinzipien der biologischen Evolution. Frommann-Holzboog, 1973.

D. E. Rumelhart, G. E. Hinton, and J. L. Mcclelland, Exploration in Parallel Distributed Processing, 1988.

K. O. Stanley and R. Miikkulainen, Evolving Neural Networks through Augmenting Topologies, Evolutionary Computation, vol.7, issue.2, pp.99-127, 2002.
DOI : 10.1016/S0096-3003(97)10005-4

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

P. J. Werbos, Beyond Regression: New Tools for Prediction and Analysis in the Behavioural Sciences, 1974.

D. Whitley, F. Gruau, and L. Pyeatt, Cellular encoding applied to neurocontrol, ICGA'95, pp.460-467, 1995.

X. Yao, Evolving artificial neural networks, Proceedings of the IEEE, vol.87, issue.9, pp.1423-1447, 1999.