D. V. Arnold, Noisy Optimization With Evolution Strategies, 2002.

H. Beyer, Toward a theory of evolution strategies: On the benefits of sex -the (µ/µ, ?) theory, Evolutionary Computation, vol.3, issue.1, pp.81-111, 1995.

N. Bredeche, E. Haasdijk, and A. Prieto, Embodied evolution in collective robotics: A review. Front, Robo. and AI, vol.5, p.12, 2018.

N. Bredeche and J. Montanier, Environment-driven Embodied Evolution in a Population of Autonomous Agents, Proc. PPSN 2010, pp.290-299, 2010.
URL : https://hal.archives-ouvertes.fr/inria-00506771

N. Bredeche, J. Montanier, B. Weel, and E. Haasdijk, Roborobo! a fast robot simulator for swarm and collective robotics, 2013.

A. Iñaki-fernández-pèrez, F. Boumaza, and . Charpillet, Comparison of selection methods in on-line distributed evolutionary robotics, Proc. of Alife'14, pp.282-289, 2014.

A. Iñaki-fernández-pèrez, F. Boumaza, and . Charpillet, Decentralized innovation marking for neural controllers in embodied evolution, Proc. of GECCO '15, pp.161-168, 2015.

N. Hansen and A. Ostermeier, Completely derandomized selfadaptation in evolution strategies, Evol. Comput, vol.9, issue.2, pp.159-195, 2001.

G. Karafotias, E. Haasdijk, and A. E. Eiben, An algorithm for distributed on-line, on-board evolutionary robotics, Proc. of GECCO '11, pp.171-178, 2011.

D. J. Schaffer, D. Whitley, and L. J. Eshelman, Combinations of genetic algorithms and neural networks: a survey of the state of the art, Proc. of COGANN '92, pp.1-37, 1992.

F. Silva, P. Urbano, and S. Oliveira, and Anders Lyhne Christensen. odneat: an algorithm for distributed online, onboard evolution of robot behaviours, Artificial Life, vol.13, pp.251-258, 2012.

O. Kenneth, R. Stanley, and . Miikkulainen, Evolving neural networks through augmenting topologies, Evol. Comput, vol.10, issue.2, pp.99-127, 2002.

R. Watson, S. Ficici, and J. Pollack, Embodied evolution: Distributing an evolutionary algorithm in a population of robots, Rob. and Auto. Sys, vol.39, pp.1-18, 2002.