A. Auger and N. Hansen, Performance Evaluation of an Advanced Local Search Evolutionary Algorithm, 2005 IEEE Congress on Evolutionary Computation, 2005.
DOI : 10.1109/CEC.2005.1554903

W. Banzhaf, Artificial Regulatory Networks and Genetic Programming, Genetic Programming Theory and Practice, pp.43-62, 2003.
DOI : 10.1007/978-1-4419-8983-3_4

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, pp.982-989, 2007.
DOI : 10.1145/1276958.1277156
URL : https://hal.archives-ouvertes.fr/inria-00145336

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

F. J. Gomez and R. Miikkulainen, Solving non-markovian control tasks with neuroevolution, IJCAI, pp.1356-1361, 1999.

F. Gruau, D. Whitley, and L. Pyeatt, A comparison between cellular encoding and direct encoding for genetic neural networks, Proc. GP'96, pp.81-89, 1996.

N. Hansen and S. Kern, Evaluating the CMA Evolution Strategy on Multimodal Test Functions, PPSN VIII, pp.282-291, 2004.
DOI : 10.1007/978-3-540-30217-9_29

N. Hansen and A. Ostermeier, Adapting arbitrary normal mutation distributions in evolutionstrategies: the covariance matrix adaptation, Proc. CEC'96, pp.312-317, 1996.

N. Hansen and A. Ostermeier, Completely Derandomized Self-Adaptation in Evolution Strategies, Evolutionary Computation, vol.9, issue.2, pp.159-195, 2001.
DOI : 10.1016/0004-3702(95)00124-7

K. Ishu, T. Van-der-zant, V. Becanovic, and P. Ploger, Identification of motion with echo state network, Oceans '04 MTS/IEEE Techno-Ocean '04 (IEEE Cat. No.04CH37600), pp.1205-1210, 2004.
DOI : 10.1109/OCEANS.2004.1405751

H. Jaeger, The Echo State Approach to Analysing and Training Recurrent Neural Networks, 2001.

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

J. Schmidhuber, D. Wierstra, M. Gagliolo, and F. Gomez, Training Recurrent Networks by Evolino, Neural Computation, vol.3, issue.3, pp.757-779, 2007.
DOI : 10.1002/int.4550080406
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.218.3086

K. Stanley, Compositional pattern producing networks: A novel abstraction of development, Genetic Programming and Evolvable Machines, vol.1143, issue.2, pp.131-162, 2007.
DOI : 10.1007/s10710-007-9028-8

K. O. Stanley and R. Miikkulainen, Efficient reinforcement learning through evolving neural network topologies, Proc. GECCO'02, pp.569-577, 2002.

D. Xu, J. Lan, and J. Principe, Direct adaptive control: an echo state network and genetic algorithm approach, Proc. IEEE International Joint Conference on Neural Networks IJCNN '05, pp.1483-1486, 2005.