D. Meunier, R. Lambiotte, and E. Bullmore, Modular and hierarchically modular organization of brain networks . Frontiers in neuroscience, p.21151783, 2010.

D. Meunier, R. Lambiotte, A. Fornito, K. Ersche, and E. Bullmore, Hierarchical modularity in human brain functional networks, Frontiers in Neuroinformatics, vol.3, 2009.
DOI : 10.3389/neuro.11.037.2009

W. Miller and . Iii, The hierarchical structure of ecosystems: connections to evolution. Evolution: Education and Outreach, pp.16-24, 2008.

E. Ravasz, A. Somera, D. Mongru, Z. Oltvai, and A. Barabási, Hierarchical Organization of Modularity in Metabolic Networks, Science, vol.297, issue.5586, pp.1551-1556, 2002.
DOI : 10.1126/science.1073374

H. Yu and M. Gerstein, Genomic analysis of the hierarchical structure of regulatory networks, Proceedings of the National Academy of Sciences, vol.103, issue.40, pp.14724-14755, 2006.
DOI : 10.1073/pnas.0508637103

R. Rowe, G. Creamer, S. Hershkop, and S. Stolfo, Automated social hierarchy detection through email network analysis, Proceedings of the 9th WebKDD and 1st SNA-KDD 2007 workshop on Web mining and social network analysis , WebKDD/SNA-KDD '07, pp.109-117, 2007.
DOI : 10.1145/1348549.1348562

P. Krugman, Confronting the mystery of urban hierarchy Journal of the Japanese and International economies, pp.399-418, 1996.

R. Guimera, L. Danon, A. Diaz-guilera, F. Giralt, and A. Arenas, Self-similar community structure in a network of human interactions. Physical review E, Dec, vol.17, issue.686, 2003.

A. Vázquez, R. Pastor-satorras, and A. Vespignani, Large-scale topological and dynamical properties of the Internet, Physical Review E, vol.65, issue.6, 2002.
DOI : 10.1103/PhysRevE.65.066130

E. Ravasz and A. Barabási, Hierarchical organization in complex networks, Physical Review E, vol.67, issue.2, 2003.
DOI : 10.1103/PhysRevE.67.026112

E. Mones, L. Vicsek, and T. Vicsek, Hierarchy measure for complex networks. PloS one, p.22470477, 2012.

D. Pumain, Hierarchy in natural and social sciences, 2006.
DOI : 10.1007/1-4020-4127-6

D. Lane, Hierarchy, Complexity, Society, Hierarchy in natural and social sciences, pp.81-119, 2006.
DOI : 10.1007/1-4020-4127-6_5

M. Sales-pardo, R. Guimera, A. Moreira, and L. Amaral, Extracting the hierarchical organization of complex systems, Proceedings of the National Academy of Sciences, pp.15224-15233, 2007.
DOI : 10.1073/pnas.0703740104

D. Lorenz, A. Jeng, and M. Deem, The emergence of modularity in biological systems Physics of life reviews, pp.129-60, 2011.

D. Bassett, D. Greenfield, A. Meyer-lindenberg, D. Weinberger, S. Moore et al., Efficient Physical Embedding of Topologically Complex Information Processing Networks in Brains and Computer Circuits, PLoS Computational Biology, vol.296, issue.4, p.20421990, 2010.
DOI : 10.1371/journal.pcbi.1000748.s001

J. Clune, J. Mouret, and H. Lipson, The evolutionary origins of modularity, Proceedings of the Royal Society B: Biological Sciences, vol.19, issue.2, 1755.
DOI : 10.1162/EVCO_a_00025
URL : https://hal.archives-ouvertes.fr/hal-01300705

P. Verbancsics and K. Stanley, Constraining connectivity to encourage modularity in HyperNEAT, Proceedings of the 13th annual conference on Genetic and evolutionary computation, GECCO '11, pp.1483-1490, 2011.
DOI : 10.1145/2001576.2001776

H. Lipson, Principles of modularity, regularity, and hierarchy for scalable systems, Journal of Biological Physics and Chemistry, vol.7, issue.4, 2007.
DOI : 10.4024/40701.jbpc.07.04

G. Wagner, M. Pavlicev, and J. Cheverud, The road to modularity, Nature Reviews Genetics, vol.24, issue.12, pp.921-952, 2007.
DOI : 10.1038/nrg2267

M. Kaiser, C. Hilgetag, and R. Kötter, Hierarchy and dynamics of neural networks. Frontiers in neuroinformatics, 2010.

N. Suh, The principles of design, 1990.

H. Ozaktas, Paradigms of connectivity for computer circuits and networks. Optical Engineering, pp.1563-1570, 1992.

A. Trusina, S. Maslov, P. Minnhagen, and K. Sneppen, Hierarchy measures in complex networks. Physical review letters, p.15169201, 2004.
DOI : 10.1103/physrevlett.92.178702
URL : http://arxiv.org/abs/cond-mat/0308339

B. Corominas-murtra, C. Rodríguez-caso, J. Goñi, and R. Solé, Measuring the hierarchy of feedforward networks, Chaos: An Interdisciplinary Journal of Nonlinear Science, vol.21, issue.1, 2011.
DOI : 10.1063/1.3562548

M. Dehmer, S. Borgert, and F. Emmert-streib, Entropy bounds for hierarchical molecular networks. PLoS One, p.18769487, 2008.

C. Song, S. Havlin, and H. Makse, Origins of fractality in the growth of complex networks. Nature Physics, Apr, vol.1, issue.24, pp.275-81, 2006.

A. Ryazanov, Dynamics of hierarchical systems, Soviet Physics Uspekhi, vol.31, issue.3, pp.286-287, 1070.
DOI : 10.1070/PU1988v031n03ABEH005744

B. Corominas-murtra, J. Goñi, R. Solé, and C. Rodríguez-caso, On the origins of hierarchy in complex networks, Proceedings of the National Academy of Sciences, pp.13316-13337, 2013.
DOI : 10.1073/pnas.1300832110

O. Neill and R. , A hierarchical concept of ecosystems, 1986.

J. Wu and J. David, A spatially explicit hierarchical approach to modeling complex ecological systems: theory and applications, Ecological Modelling, vol.153, issue.1-2, pp.7-26, 2002.
DOI : 10.1016/S0304-3800(01)00499-9

J. Flack, D. Erwin, T. Elliot, and D. Krakauer, Timescales, symmetry, and uncertainty reduction in the origins of hierarchy in biological systems. Evolution cooperation and complexity, Feb, vol.22, pp.45-74, 2013.

S. Salthe, Evolving hierarchical systems: their structure and representation. Columbia University Press, 2013.

J. Sun and M. Deem, Spontaneous emergence of modularity in a model of evolving individuals. Physical review letters, p.18233336, 2007.

M. Pigliucci, Is evolvability evolvable?, Nature Reviews Genetics, vol.49, issue.1, pp.75-82, 2008.
DOI : 10.1038/nrg2278

J. Clune, . Beckmann, . Be, . Mckinley, . Pk et al., Investigating whether hyperNEAT produces modular neural networks, Proceedings of the 12th annual conference on Genetic and evolutionary computation, GECCO '10, pp.635-642, 2010.
DOI : 10.1145/1830483.1830598

R. Paine and T. J. , How Hierarchical Control Self-organizes in Artificial Adaptive Systems, Adaptive Behavior, vol.13, issue.3, pp.211-236, 2005.
DOI : 10.1177/105971230501300303

J. Huizinga, J. Mouret, and J. Clune, Evolving neural networks that are both modular and regular, Proceedings of the 2014 conference on Genetic and evolutionary computation, GECCO '14, 2014.
DOI : 10.1145/2576768.2598232
URL : https://hal.archives-ouvertes.fr/hal-01300699

C. Cherniak, Z. Mokhtarzada, R. Rodriguez-esteban, and K. Changizi, Global optimization of cerebral cortex layout, Proceedings of the National Academy of Sciences, vol.101, issue.4, pp.1081-1086, 2004.
DOI : 10.1073/pnas.0305212101

B. Chen, D. Hall, and D. Chklovskii, Wiring optimization can relate neuronal structure and function, Proceedings of the National Academy of Sciences, pp.4723-4731, 2006.
DOI : 10.1073/pnas.0506806103

A. Raj and Y. Chen, The Wiring Economy Principle: Connectivity Determines Anatomy in the Human Brain, PLoS ONE, vol.2, issue.4, p.21915250, 2011.
DOI : 10.1371/journal.pone.0014832.s006

Y. Ahn, H. Jeong, and B. Kim, Wiring cost in the organization of a biological neuronal network. Physica A: Statistical Mechanics and its Applications, Jul, vol.15, issue.367, pp.531-538, 2006.

S. Laughlin and T. Sejnowski, Communication in neuronal networks. Science, pp.1870-1874, 2003.

R. Guimera, A. Arenas, and A. Diaz-guilera, Communication and optimal hierarchical networks. Physica A: Statistical Mechanics and its Applications, pp.247-52, 2001.

H. Simon, The architecture of complexity, Proceedings of the American Philosophical Society, 1962.

R. Lenski, C. Ofria, T. Collier, and C. Adami, Genome complexity, robustness and genetic interactions in digital organisms, Nature Aug, vol.12, issue.4006745, pp.661-665, 1999.

R. Lenski, C. Ofria, R. Pennock, and C. Adami, The evolutionary origin of complex features, Nature, vol.148, issue.6936, pp.139-183, 1568.
DOI : 10.1038/35076523

C. Wilke, J. Wang, C. Ofria, R. Lenski, and C. Adami, Evolution of digital organisms at high mutation rates leads to survival of the flattest, Nature, vol.412, issue.6844, pp.331-334, 2001.
DOI : 10.1038/35085569

C. Espinosa-soto and A. Wagner, Specialization Can Drive the Evolution of Modularity, PLoS Computational Biology, vol.103, issue.3, p.20360969, 2010.
DOI : 10.1371/journal.pcbi.1000719.s008

N. Kashtan and U. Alon, Spontaneous evolution of modularity and network motifs, Proceedings of the National Academy of Sciences, pp.13773-13781, 2005.
DOI : 10.1073/pnas.0503610102

N. Kashtan, E. Noor, and U. Alon, Varying environments can speed up evolution, Proceedings of the National Academy of Sciences, vol.104, issue.34, pp.13711-13717, 2007.
DOI : 10.1073/pnas.0611630104

U. Alon, An introduction to systems biology: design principles of biological circuits, 2006.

T. Trappenberg, Fundamentals of computational neuroscience, 2009.

N. Geard and J. Wiles, A Gene Network Model for Developing Cell Lineages, Artificial Life, vol.11, issue.3, pp.249-67, 2005.
DOI : 10.1074/jbc.M104391200

J. Mouret and J. Clune, Illuminating search spaces by mapping elites. arXiv preprint

A. Cully, J. Clune, D. Tarapore, and J. Mouret, Robots that can adapt like animals, Nature, vol.26, issue.7553, pp.503-507, 2015.
DOI : 10.1038/nrn2332
URL : https://hal.archives-ouvertes.fr/hal-01158243

M. Kaiser and C. Hilgetag, Nonoptimal Component Placement, but Short Processing Paths, due to Long-Distance Projections in Neural Systems, PLoS Computational Biology, vol.21, issue.7, p.16848638, 2006.
DOI : 10.1371/journal.pcbi.0020095.sg003

R. Louf, P. Jensen, and M. Barthelemy, Emergence of hierarchy in cost-driven growth of spatial networks, Proceedings of the National Academy of Sciences, pp.8824-8833, 2013.
DOI : 10.1073/pnas.1222441110

Y. Zhang, Z. Huang, Z. Zhu, J. Liu, X. Zheng et al., Network analysis of ChIP-Seq data reveals key genes in prostate cancer European journal of medical research, pp.47-25183411, 2014.

I. Shmulevich, E. Dougherty, S. Kim, and W. Zhang, Probabilistic Boolean networks: a rule-based uncertainty model for gene regulatory networks, Bioinformatics, vol.18, issue.2, pp.261-74, 2002.
DOI : 10.1093/bioinformatics/18.2.261

R. Albert, Scale-free networks in cell biology Journal of cell science, pp.4947-57, 2005.

J. Koza, M. Keane, M. Streeter, W. Mydlowec, J. Yu et al., Genetic programming IV: Routine human-competitive machine intelligence, 2006.

D. Floreano and C. Mattiussi, Bio-inspired artificial intelligence: theories, methods, and technologies, 2008.

K. Stanley and R. Miikkulainen, A Taxonomy for Artificial Embryogeny, Artificial Life, vol.13, issue.1, pp.93-130, 2003.
DOI : 10.1002/cne.902460104

G. Hornby, Measuring, enabling and comparing modularity, regularity and hierarchy in evolutionary design, Proceedings of the 2005 conference on Genetic and evolutionary computation , GECCO '05, 2005.
DOI : 10.1145/1068009.1068297

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.346-67, 2010.
DOI : 10.1109/TEVC.2010.2104157

F. Gruau, Automatic definition of modular neural networks Adaptive behavior, pp.151-83, 1994.

S. Nolfi and D. Floreano, Evolutionary Robotics, 2000.
DOI : 10.1007/978-3-319-32552-1_76

G. Striedter, Principles of brain evolution Sinauer Associates, 2005.

G. Wagner and L. Altenberg, Perspective: Complex Adaptations and the Evolution of Evolvability, Evolution, vol.50, issue.3, pp.967-76, 1996.
DOI : 10.2307/2410639

K. Stanley, D. Ambrosio, D. Gauci, and J. , A hypercube-based encoding for evolving large-scale neural networks . Artificial life, pp.185-212, 2009.

K. Deb, Multi-objective optimization using evolutionary algorithms, 2001.

J. Mouret and S. Doncieux, Overcoming the bootstrap problem in evolutionary robotics using behavioral diversity, 2009 IEEE Congress on Evolutionary Computation, pp.1161-1168, 2009.
DOI : 10.1109/CEC.2009.4983077
URL : https://hal.archives-ouvertes.fr/hal-00473147

S. Doncieux and J. Mouret, Behavioral diversity measures for Evolutionary Robotics, IEEE Congress on Evolutionary Computation, pp.1-8, 2010.
DOI : 10.1109/CEC.2010.5586100
URL : https://hal.archives-ouvertes.fr/hal-00687641

J. Mouret and S. Doncieux, Encouraging behavioral diversity in evolutionary robotics: An empirical study. Evolutionary computation, pp.91-133, 2012.
URL : https://hal.archives-ouvertes.fr/hal-00687609

S. Risi, . Vanderbleek, . Sd, C. Hughes, and K. Stanley, How novelty search escapes the deceptive trap of learning to learn, Proceedings of the 11th Annual conference on Genetic and evolutionary computation, GECCO '09, pp.153-160, 2009.
DOI : 10.1145/1569901.1569923

D. Chklovskii, Exact solution for the optimal neuronal layout problem Neural computation, pp.2067-78, 2004.

J. Lehman and K. Stanley, Abandoning objectives: Evolution through the search for novelty alone. Evolutionary computation, pp.189-223, 2011.

G. Karlebach and R. Shamir, Modelling and analysis of gene regulatory networks, Nature Reviews Molecular Cell Biology, vol.18, issue.10, pp.770-80, 2008.
DOI : 10.1038/nrm2503

E. Leicht and M. Newman, Community structure in directed networks Physical review letters, p.18517839, 2008.

M. Newman, Modularity and community structure in networks, Proceedings of the national academy of sciences, pp.8577-82, 2006.
DOI : 10.1073/pnas.0601602103

D. Czégel and G. Palla, Random walk hierarchy measure: What is more hierarchical, a chain, a tree or a star? Scientific reports, 2015.

J. Mouret and S. Doncieux, Sferes v2: Evolvin'in the multi-core world, Evolutionary Computation 2010 IEEE Congress on, pp.1-8
URL : https://hal.archives-ouvertes.fr/hal-00687633