E. Alba and M. Tomassini, Parallelism and evolutionary algorithms, IEEE Transactions on Evolutionary Computation, vol.6, issue.5, pp.443-462, 2002.
DOI : 10.1109/TEVC.2002.800880

G. Guner-alpaydtn, S. Dundar, and . Balktr, Evolution-based design of neural fuzzy networks using self-adapting genetic parameters, IEEE Transactions on Fuzzy Systems, vol.10, issue.2, pp.211-221, 2002.
DOI : 10.1109/91.995122

P. Angeline, Genetic programming's continued evolution Advances in genetic programming, pp.1-20, 1996.

P. Angeline, Two self-adaptive crossover operators for genetic programming Advances in genetic programming, pp.89-109, 1996.

J. Antonisse, A new interpretation of schema notation that overturns the binary encoding constraint, International Conference of Genetic Algorithms, pp.86-91

I. Babuska and J. L. Melenk, The partition of unity finite element method, 1995.

R. Babu?ka, Fuzzy Modeling, Fuzzy Logic Control: Advances in Methodology, pp.187-220, 1998.
DOI : 10.1007/978-94-011-4868-9_2

T. Back, Introduction to evolutionary algorithms and their instances, Handbook of Evolutionary Computation, 1997.

T. Back, D. Fogel, D. Whitley, and P. Angeline, Mutation Handbook of Evolutionary Computation, Ulrich Hammel, and Hans-Paul Schwefel. Evolutionary computation: Comments on the history and current state, pp.1-15, 1997.

T. Back, G. Rudolph, and H. Schwefel, Evolutionary programming and evolution strategies: Similarities and differences, Proceedings of the Second Annual Conference on Evolutionary Programming, pp.11-22, 1993.

T. Back and M. Shutz, Evolution strategies for mixed-integer optimization of optical multilayer systems, Proceedings of the 4th International Conference on Evolutionary Programming, pp.33-51, 1995.

A. G. Barto, R. S. Sutton, and C. W. Anderson, Neuronlike adaptive elements that can solve difficult learning control problems, IEEE Transactions on Systems, Man, and Cybernetics, vol.13, issue.5, pp.834-846, 1983.
DOI : 10.1109/TSMC.1983.6313077

J. Bassett and K. , Evolving Behaviors for Cooperating Agents, Proceedings of the ISMIS 2000, pp.157-165, 2000.
DOI : 10.1007/3-540-39963-1_17

J. Bassett, M. Potter, and K. , Looking Under the EA Hood with Price???s Equation, Proceedings of the Genetic and Evolutionary Computation GECCO, pp.914-922, 2004.
DOI : 10.1007/978-3-540-24854-5_92

E. Benoit, Capteurs symboliques et capteurs flous : un nouveau pas vers l'intelligence, 1993.

E. Benoit, G. Mauris, and L. Foulloy, FUZZY SENSOR AGGREGATION: APPLICATION TO COMFORT MEASUREMENT, Proceedings of the IPMU, pp.721-726, 1994.
DOI : 10.1142/9789812830753_0026
URL : https://hal.archives-ouvertes.fr/hal-00143847

E. Benoit, G. Mauris, and L. Foulloy, A fuzzy colour sensor, Proceedings of the 13th IMEKO, pp.1015-1020, 1994.
URL : https://hal.archives-ouvertes.fr/hal-00008819

H. Berenji and P. Khedkar, Learning and tuning fuzzy logic controllers through reinforcements, IEEE Transactions on Neural Networks, vol.3, issue.5, pp.724-740, 1992.
DOI : 10.1109/72.159061

J. Bezdek, Fuzzy models—What are they, and why? [Editorial], IEEE Transactions on Fuzzy Systems, vol.1, issue.1, pp.1-6, 1993.
DOI : 10.1109/TFUZZ.1993.6027269

C. Bishop, Neural Networks for Pattern Recognition, 1995.

L. Booker, D. Fogel, D. Whitley, and P. Angeline, Recombination, Handbook of Evolutionary Computation, 1997.
URL : https://hal.archives-ouvertes.fr/jpa-00219020

R. Brooks, Intelligence without reason. AI Lab memo 1293, 1991.

E. Cantu-paz, Efficient and Accurate Parallel Genetic Algorithms, 2000.
DOI : 10.1007/978-1-4615-4369-5

P. Carinena, C. Regueiro, A. Otero, A. Bugarin, and S. Barro, Landmark Detection in Mobile Robotics Using Fuzzy Temporal Rules, IEEE Transactions on Fuzzy Systems, vol.12, issue.4, pp.423-435, 2004.
DOI : 10.1109/TFUZZ.2004.832534

. Doo-hyun, S. Choi, and . Oh, A new mutation rule for evolutionary programming motivated from backpropagation learning, IEEE Transactions on Evolutionary Computation, vol.4, issue.2, pp.188-190, 2000.
DOI : 10.1109/4235.850659

O. Cordóncord´cordón, F. Herrera, and P. Villar, Generating the knowledge base of a fuzzy rule-based system by the genetic learning of the data base, IEEE Transactions on Fuzzy Systems, vol.9, issue.4, pp.667-674, 2001.
DOI : 10.1109/91.940977

F. Gomide, F. Herrera, F. Hoffmann, and L. Magdalena, Ten years of genetic fuzzy systems: Current framework and new trends. Fuzzy Sets and Systems, Oscar Cord¨?¿Cord¨?¿ 1 2, pp.5-31, 2004.

N. Cramer, A representation for the adaptive generation of simple sequential programs, Proceedings of the International Conference on Genetic Algorithms and their Applications, pp.183-187, 1985.

M. De-berg, M. Van-kreveld, M. Overmars, and O. Schwarzkopf, Computational Geometry , Algorithms and Applications, 1998.

J. Kenneth-de, Evolutionary Computation: a Unified Approach, 2006.

K. Deb, Introduction to representations of evolutionary computation models, Handbook of Evolutionary Computation, 1997.

K. Deb, Multi-Objective Optimization Using Evolutionary Algorithms, 2001.

K. Deb and R. Agrawal, Simulated binary crossover for continuous search space, Complex Systems, vol.9, pp.115-148, 1995.

J. Dickerson and B. Kosko, Fuzzy function approximation with ellipsoidal rules, IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics), vol.26, issue.4, pp.542-560, 1996.
DOI : 10.1109/3477.517030

F. Divina and E. Marchiori, Evolutionary concept learning, Proceedings of the Genetic and Evolutionary Computation Conference GECCO, pp.343-350, 2002.

D. Dracopoulos, Evolutionary Learning Algorithms for Neural Adaptive Control, 1997.
DOI : 10.1007/978-1-4471-0903-7

A. E. Eiben and C. A. Schippers, On evolutionary exploration and exploitation, Fundamenta Informaticae, vol.35, pp.1-16, 1998.

A. Eiben, Evolutionary computing, Dutch Mathematical Archive, pp.126-131, 2002.
DOI : 10.1016/S0020-0190(02)00204-1
URL : https://hal.archives-ouvertes.fr/inria-00000542

A. Eiben, R. Hinterding, and Z. Michalewicz, Parameter control in evolutionary algorithms, IEEE Transactions on Evolutionary Computation, vol.3, issue.2, pp.124-141, 1999.
DOI : 10.1109/4235.771166
URL : https://hal.archives-ouvertes.fr/inria-00140549

A. Eiben and M. Schoenauer, Evolutionary computing, Information Processing Letters, vol.82, issue.1, pp.1-6, 2000.
DOI : 10.1016/S0020-0190(02)00204-1
URL : https://hal.archives-ouvertes.fr/inria-00000542

A. Eiben and J. E. Smith, Introduction to Evolutionary Computing, 2003.

L. Eshelman, Genetic algorithms, Handbook of Evolutionary Computation, 1997.

S. Farinwata, D. Filev, and R. Langari, Fuzzy Control, Synthesis and Analysis, 2000.

G. Feng, An approach to adaptive control of fuzzy dynamic systems, IEEE Transactions on Fuzzy Systems, vol.10, issue.2, pp.268-275, 2002.
DOI : 10.1109/91.995127

D. Floreano and F. Mondada, Evolution of homing navigation in a real mobile robot, IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics), vol.26, issue.3, pp.396-407, 1996.
DOI : 10.1109/3477.499791

D. Fogel, ASYMPTOTIC CONVERGENCE PROPERTIES OF GENETIC ALGORITHMS AND EVOLUTIONARY PROGRAMMING: ANALYSIS AND EXPERIMENTS, Cybernetics and Systems, vol.9, issue.3, pp.389-407, 1994.
DOI : 10.1080/01969729408902335

D. Fogel, Principles of evolutionary processes, Handbook of Evolutionary Computation, 1997.

A. Freitas, A Survey of Evolutionary Algorithms for Data Mining and Knowledge Discovery, 2003.
DOI : 10.1007/978-3-642-18965-4_33

S. Galichet and L. Foulloy, Fuzzy controllers: synthesis and equivalences, IEEE Transactions on Fuzzy Systems, vol.3, issue.2, pp.140-148, 1995.
DOI : 10.1109/91.388169
URL : https://hal.archives-ouvertes.fr/hal-00482858

J. Garnier, L. Kallel, and M. Schoenauer, Rigorous Hitting Times for Binary Mutations, Evolutionary Computation, vol.5, issue.3, pp.167-203, 1999.
DOI : 10.1162/evco.1996.4.2.195
URL : https://hal.archives-ouvertes.fr/inria-00001277

J. Godjevac, Comparative study of fuzzy control, neural network control and neurofuzzy control, Fuzzy Set Theory and Advanced Mathematical Applications, pp.291-322, 1995.

D. Goldberg, Genetic Algorithms in Search, Optimization, and Machine Learning, 1989.

J. Grefenstette, The Evolution of Strategies for Multiagent Environments, Adaptive Behavior, vol.1, issue.1, pp.65-89, 1992.
DOI : 10.1177/105971239200100104

J. Grefenstette, Proportional selection and sampling algorithms, Handbook of Evolutionary Computation, 1997.
DOI : 10.1887/0750308958/b386c30

J. Grefenstette, Rank-based selection, Handbook of Evolutionary Computation, 1997.

R. Gunter, Evolution strategies, Handbook of Evolutionary Computation, 1997.

N. Hansen, S. Mller, and P. Koumoutsakos, Reducing the Time Complexity of the Derandomized Evolution Strategy with Covariance Matrix Adaptation (CMA-ES), Evolutionary Computation, vol.11, issue.1, 2003.
DOI : 10.1162/106365601750190398

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

S. Haykin, Neural Networks. A Comprehensive Foundation, 1999.

J. Hekanaho, DOGMA: A GA-based relational learner, Proceedings of the 8th International Conference on Inductive Logic Programming, pp.205-214, 1998.
DOI : 10.1007/BFb0027324

F. Hoffmann, Evolutionary algorithms for fuzzy control system design, Proceedings of the IEEE, pp.1318-1333, 2001.
DOI : 10.1109/5.949487

M. Hojati and S. Gazor, Hybrid adaptive fuzzy identification and control of nonlinear systems, IEEE Transactions on Fuzzy Systems, vol.10, issue.2, pp.211-221, 2002.
DOI : 10.1109/91.995121

A. Homaifar and E. Mccormick, Simultaneous design of membership functions and rule sets for fuzzy controllers using genetic algorithms, IEEE Transactions on Fuzzy Systems, vol.3, issue.2, pp.129-139, 1995.
DOI : 10.1109/91.388168

M. Hulse, B. Lara, F. Pasemann, and U. Steinmetz, Evolving Neural Behaviour Control for Autonomous Robots, Proceedings of the ICANN, pp.957-962, 2001.
DOI : 10.1007/3-540-44668-0_132

S. Idelsohn and E. Onate, Nestor Calvo, and Facundo del Pin. The meshless finite element method, International Journal for Numerical Methods in Engineering, vol.58, issue.4, 2003.

J. Jang, ANFIS: adaptive-network-based fuzzy inference system, IEEE Transactions on Systems, Man, and Cybernetics, vol.23, issue.3, pp.665-685, 1993.
DOI : 10.1109/21.256541

C. Janikow, A knowledge-intensive genetic algorithm for supervised learning, Machine Learning, pp.189-228, 1993.

K. De, J. , and W. Spears, An overview of evolutionary computation, Proceedings of European Conference on Machine Learning, pp.442-259, 1993.

J. Kenneth-de, An Analysis of the Behavior of a class of genetic adaptive systems, 1975.

K. De, J. , and W. Spears, On the state of evolutionary computation, Proceedings of the ICGA, pp.618-625, 1993.

W. Kenneth-de-jong, D. Spears, and . Gordon, Using genetic algorithms for concept learning, Machine Learning, pp.161-188, 1993.

C. Juang and C. Lin, A recurrent self-organizing neural fuzzy inference network, IEEE Transactions on Neural Networks, vol.10, issue.4, pp.828-845, 1999.
DOI : 10.1109/72.774232

C. Juang, A TSK-type recurrent fuzzy network for dynamic systems processing by neural network and genetic algorithms, IEEE Transactions on Fuzzy Systems, vol.10, issue.2, pp.155-170, 2002.
DOI : 10.1109/91.995118

C. Juang, J. Lin, and C. Lin, Genetic reinforcement learning through symbiotic evolution for fuzzy controller design, IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics), vol.30, issue.2, pp.290-302, 2000.
DOI : 10.1109/3477.836377

C. Karr and E. Gentry, Fuzzy control of pH using genetic algorithms, IEEE Transactions on Fuzzy Systems, vol.1, issue.1, pp.46-53, 1993.
DOI : 10.1109/TFUZZ.1993.390283

N. Kasabov and Q. Song, DENFIS: dynamic evolving neural-fuzzy inference system and its application for time-series prediction, IEEE Transactions on Fuzzy Systems, vol.10, issue.2, pp.144-154, 2002.
DOI : 10.1109/91.995117

C. Kavka, M. L. Crespo, M. Cena, F. Wu-geng-feng, and . Zhong-quian, Fuzzy systems generation through symbiotic evolution, Proceedings of the International Symposium on Engineering of Intelligent Systems EIS, pp.37-44, 1998.

C. Kavka, M. L. Crespo, F. Wu-geng-feng, and . Zhong-quian, A fuzzy controller development tool based on evolutionary techniques, Proceedings of the 1999 Congress on Evolutionary Computation-CEC99 (Cat. No. 99TH8406), pp.2145-2150, 1999.
DOI : 10.1109/CEC.1999.785540

C. Kavka, P. Roggero, and M. Schoenauer, Evolution of Voronoi based fuzzy recurrent controllers, Proceedings of the 2005 conference on Genetic and evolutionary computation , GECCO '05, pp.1385-1392, 2005.
DOI : 10.1145/1068009.1068231
URL : https://hal.archives-ouvertes.fr/inria-00000539

C. Kavka and M. Schoenauer, Voronoi Diagrams Based Function Identification, Proceedings of the Genetic and Evolutionary Computation Conference GECCO, pp.1089-1100, 2003.
DOI : 10.1007/3-540-45105-6_118

C. Kavka and M. Schoenauer, Evolution of Voronoi-Based Fuzzy Controllers, Proceedings of the Conference on Parallel Problem Solving from Nature PPSN, pp.541-550, 2004.
DOI : 10.1007/978-3-540-30217-9_55
URL : https://hal.archives-ouvertes.fr/inria-00000539

C. Kennedy and C. Giraud-carrier, An Evolutionary Approach to Concept Learning with Structured Data, Proceedings of the Fourth International Conference on Artificial Neural Networks and Genetic Algorithms, pp.1-6, 1999.
DOI : 10.1007/978-3-7091-6384-9_56

S. Khuri, T. Back, and J. Heitkotter, The zero/one multiple knapsack problem and genetic algorithms, Proceedings of the 1994 ACM symposium on Applied computing , SAC '94, pp.188-193, 1994.
DOI : 10.1145/326619.326694

K. Kinnear, R. Smith, and Z. Michalewicz, Derivative methods, Handbook of Evolutionary Computation, 1997.
DOI : 10.1887/0750308958/b386c11

. Seong-gon, B. Kong, and . Kosko, Adaptive fuzzy systems for backing up a truck-andtrailer, IEEE Transactions on Neural Networks, vol.3, issue.2, pp.211-223, 1992.

B. Kosko, Fuzzy systems as universal approximators, IEEE Transactions on Computers, vol.43, issue.11, pp.1329-1333, 1994.
DOI : 10.1109/12.324566

J. Koza, Genetic programming, pp.29-43, 1998.

F. Labelle and J. Schewchuk, Anisotropic voronoi diagrams and guaranteed-quality anisotropic mesh generation, Proceedings of the nineteenth conference on Computational geometry , SCG '03, pp.191-200, 2003.
DOI : 10.1145/777792.777822

P. Luca-lanzi and R. Riolo, A roadmap to the last decade of learning classifier systems, Learning Classifier Systems: From Foundations to Applications, pp.33-61, 2000.

P. Luca-lanzi, W. Stolzmann, and S. W. Wilson, Learning Classifier Systems, From Foundations to Applications, 2000.

C. Lee and C. Teng, Identification and control of dynamic systems using recurrent fuzzy neural networks, IEEE Transactions on Fuzzy Systems, vol.8, issue.4, pp.349-366, 2000.

C. Lee, Fuzzy logic in control systems: fuzzy logic controller. I, IEEE Transactions on Systems, Man, and Cybernetics, vol.20, issue.2, pp.404-418, 1990.
DOI : 10.1109/21.52551

C. Lee, Fuzzy logic in control systems: fuzzy logic controller. I, IEEE Transactions on Systems, Man, and Cybernetics, vol.20, issue.2, pp.419-435, 1990.
DOI : 10.1109/21.52551

M. Lee and H. Takagi, Integrating design stage of fuzzy systems using genetic algorithms, [Proceedings 1993] Second IEEE International Conference on Fuzzy Systems, pp.612-617, 1993.
DOI : 10.1109/FUZZY.1993.327418

D. Leitch, A New Genetic Algorithm for the Evolution of Fuzzy Systems, 1995.

C. Lin and C. S. George-lee, Neural Fuzzy Systems: A Neural-Fuzzy Synergism to Intelligent Systems [100] D. Linkens and H. Nyongesa. Fuzzy modeling: Principles, methods and applications, Proceedings of the Control Theory Applications Conference, pp.367-386, 1986.

M. Margaliot and G. Langholz, New Approaches to Fuzzy Modeling and Control -Design and Analysis, chapter One, World Scientific, 2000.

P. Mastorocostas and J. Theocharis, A recurrent fuzzy-neural model for dynamic system identification, IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics), vol.32, issue.2, pp.176-190, 2002.
DOI : 10.1109/3477.990874

P. Mcquesten, Cultural Enhancement of Neuroevolution, 2002.

Z. Michalewicz, Genetic Algorithms + Data Structures = Evolution Programs, 1997.

Z. Michalewicz, Introduction to search operators, Handbook of Evolutionary Computation, 1997.
DOI : 10.1887/0750306645/b877c31

Z. Michalewicz, R. Hinterding, and M. Michalewicz, Evolutionary Algorithms, Fuzzy Evolutionary Computation, chapter 2. Kluwer Academic, 1997.
DOI : 10.1007/978-1-4419-1153-7_308
URL : https://hal.archives-ouvertes.fr/inria-00140549

Z. Michalewicz, T. Logan, and S. Swaminathan, Evolutionary operators for continuous convex parameter spaces, Proceedings of the Third Annual Conference on Evolutionary Programming, pp.84-97, 1994.

Z. Michalewicz, G. Nazhiyath, and M. Michalewicz, A note on usefulness of geometrical crossover for numerical optimization problems, Evolutionary Programming, pp.305-312, 1996.

Z. Michalewicz, G. Nazhiyath, and M. Michalewicz, A note on usefulness of geometrical crossover for numerical optimization problems, Proceedings of the 5th Annual Conference on Evolutionary Programming, pp.305-312, 1994.

Z. Michalewicz and M. Schoenauer, Evolutionary Algorithms for Constrained Parameter Optimization Problems, Evolutionary Computation, vol.13, issue.1, pp.1-32, 1996.
DOI : 10.1162/evco.1996.4.1.1

O. Michel, Kephera simulator package version 2.0: Freeware mobile robot simulator written at the university of nice sophia-antipolis by olivier michel. Downloadable from the World Wide Web at http

S. Mitaim and B. Kosko, The shape of fuzzy sets in adaptive function approximation, IEEE Transactions on Fuzzy Systems, vol.9, issue.4, pp.637-656, 2001.
DOI : 10.1109/91.940974

A. Mitchell, The Finite Element Method in Partial Differential Equations, 1977.

S. Mitra and Y. Hayashi, Neuro-fuzzy rule generation: survey in soft computing framework, IEEE Transactions on Neural Networks, vol.11, issue.3, pp.748-768, 2000.
DOI : 10.1109/72.846746

D. Moriarty and R. Miikulainen, Efficient reinforcement learning through symbiotic evolution, Machine Learning, pp.11-33, 1996.
DOI : 10.1007/bf00114722
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.37.4883

D. Moriarty, A. Schultz, and J. Grefenstette, Evolutionary algorithms for reinforcement learning, Journal of Artificial Intelligent Research, vol.11, pp.241-276, 1999.

G. Mouzouris and J. Mendel, Dynamic non-Singleton fuzzy logic systems for nonlinear modeling, IEEE Transactions on Fuzzy Systems, vol.5, issue.2, pp.199-208, 1997.
DOI : 10.1109/91.580795

M. Mucientes, R. Iglesias, C. Regueiro, A. Bugarin, P. Carinena et al., Fuzzy temporal rules for mobile robot guidance in dynamic environments, IEEE Transactions on Systems, Man and Cybernetics, Part C (Applications and Reviews), vol.31, issue.3, pp.31391-398, 2001.
DOI : 10.1109/5326.971667

D. Muni, P. Pal, and J. Das, A Novel Approach to Design Classifiers Using Genetic Programming, IEEE Transactions on Evolutionary Computation, vol.8, issue.2, pp.183-196, 2004.
DOI : 10.1109/TEVC.2004.825567

H. Nguyen, N. Prasad, C. Walker, and E. Walker, A First Course in Fuzzy and Neural Control, 2003.
DOI : 10.1201/9781420035520

S. Nolfi and D. Floreano, The Biology, Intelligence, and Technology of Self-Organizing Machines, Evolutionary Robotics, 2000.

T. Pal, Sogarg: a self-organized genetic algorithm-based rule generation scheme for fuzzy controllers, IEEE Transactions on Evolutionary Computation, vol.7, issue.4, pp.397-415, 2003.
DOI : 10.1109/TEVC.2003.815377

W. Porto, Evolutionary programming, Handbook of Evolutionary Computation, 1997.

A. Rajapakse, K. Furuta, and S. Kondo, Evolutionary learning of fuzzy logic controllers and their adaptation through perpetual evolution, IEEE Transactions on Fuzzy Systems, vol.10, issue.3, pp.309-321, 2002.
DOI : 10.1109/TFUZZ.2002.1006434

I. Rechenberg, Evolutionstrategie: Optimierung Technisher Systeme nach Prinzipien des Biologischen Evolution, 1972.

A. Saffiotti, The uses of fuzzy logic in autonomous robot navigation, Soft Computing - A Fusion of Foundations, Methodologies and Applications, vol.1, issue.4, pp.180-197, 1997.
DOI : 10.1007/s005000050020

S. Schaal and C. Atkeson, Constructive Incremental Learning from Only Local Information, Neural Computation, vol.26, issue.8, pp.2047-2084, 1998.
DOI : 10.1080/03610927508827223

M. Schoenauer, F. Jouve, and L. Kallel, Identification of Mechanical Inclusions, Evolutionary Algorithms in Engineering Applications, 1997.
DOI : 10.1007/978-3-662-03423-1_26

M. Schoenauer, Habilitation dissertation. Equipe Evolution Artificielle et Apprentissage, 1997.

H. Schwefel, Numerical Optimization of Computer Models, 1981.

H. Schwefel, Advantages (and disadvantages) of evolutionary computation over other approaches, Handbook of Evolutionary Computation, 1997.

H. Schwefel and R. Gunter, Contemporary evolution strategies, Advances in Artificial Life, pp.893-907, 1995.
DOI : 10.1007/3-540-59496-5_351

M. Teo-lian-seng, R. Khalid, and . Yusof, Tuning of a neuro-fuzzy controller by genetic algorithm, IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics), vol.29, issue.2, pp.226-236, 1999.
DOI : 10.1109/3477.752795

M. Setnes and R. Babu?ka, Fuzzy modeling for predictive control, Fuzzy Control, 2000.

R. Smith, T. Back, and W. Spears, Heuristics for parameter settings, Handbook of Evolutionary Computation, 1997.

W. Spears, Recombination parameters, Handbook of Evolutionary Computation, 1997.

W. Spears, K. D. Jong, T. Back, D. Fogel, and H. Garis, An overview of evolutionary computation, ECML '93: Proceedings of the European Conference on Machine Learning, pp.442-459, 1993.
DOI : 10.1007/3-540-56602-3_163

N. Sukumar, B. Moran, and T. Belytschko, The natural element method in solid mechanics, International Journal for Numerical Methods in Engineering, vol.27, issue.5, pp.839-887, 1998.
DOI : 10.1002/(SICI)1097-0207(19981115)43:5<839::AID-NME423>3.0.CO;2-R

Y. Lei, S. , and M. Er, Hybrid fuzzy control of robotic systems, IEEE Transactions on Fuzzy Systems, vol.12, issue.6, pp.755-765, 2004.

P. Surry and N. Radcliffe, Formal algorithms + formal representations =search strategies, Proceedings of the 3th Parallel Problem Solving from Nature, pp.366-375, 1996.
DOI : 10.1007/3-540-61723-X_1001

P. Surry and N. Radcliffe, Real representations, Foundations of Genetic Algorithms IV, 1996.

T. Takagi and M. Sugeno, Fuzzy identification of systems and its applications to modeling and control, IEEE Transactions on Systems, Man, and Cybernetics, vol.15, issue.1, pp.116-132, 1985.
DOI : 10.1109/TSMC.1985.6313399

G. Biing-tsair-tien and . Van-straten, The incorporation of qualitative information into T-S fuzzy model, 1997 Annual Meeting of the North American Fuzzy Information Processing Society, NAFIPS (Cat. No.97TH8297), pp.148-153, 1997.
DOI : 10.1109/NAFIPS.1997.624027

G. Vachkov, Adaptive and learning schemes for fuzzy modeling, Synthesis and Analysis, pp.47-72, 2000.

L. Wang and J. Mendel, Fuzzy basis functions, universal approximation, and orthogonal least-squares learning, IEEE Transactions on Neural Networks, vol.3, issue.5, pp.807-814, 1992.
DOI : 10.1109/72.159070

S. Wilson, Classifier Fitness Based on Accuracy, Evolutionary Computation, vol.2, issue.3, pp.149-175, 1995.
DOI : 10.1162/evco.1994.2.1.1

S. Wilson and D. Goldberg, A critical review of classifier systems, Proceedings of the Third International Conference on Genetic Algorithms, pp.244-255, 1989.

D. Withely and J. Kauth, Genitor: A different genetic algorithm, 1988.

D. Wolpert and W. Macready, No free lunch theorems for search, 1996.

X. Yao, A review of evolutionary artificial neural networks, International Journal of Intelligent Systems, vol.1, issue.4, pp.203-222, 1993.
DOI : 10.1002/int.4550080406

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

J. Yen and N. Pfluger, A fuzzy logic based extension to Payton and Rosenblatt's command fusion method for mobile robot navigation, IEEE Transactions on Systems, Man, and Cybernetics, vol.25, issue.6, pp.971-978, 1995.
DOI : 10.1109/21.384260

H. Ying, General SISO Takagi-Sugeno fuzzy systems with linear rule consequent are universal approximators, IEEE Transactions on Fuzzy Systems, vol.6, issue.4, pp.582-587, 1988.
DOI : 10.1109/91.728456

H. Ying, Constructing nonlinear variable gain controllers via the Takagi-Sugeno fuzzy control, IEEE Transactions on Fuzzy Systems, vol.6, issue.2, pp.226-234, 1998.
DOI : 10.1109/91.669021

L. Zadeh, Fuzzy sets, Information and Control, vol.8, issue.3, pp.338-353, 1965.
DOI : 10.1016/S0019-9958(65)90241-X

L. Zadeh, Fuzzy algorithms, Information and Control, vol.12, issue.2, pp.94-102, 1968.
DOI : 10.1016/S0019-9958(68)90211-8

L. Zadeh, Fuzzy logic, Computer, vol.21, issue.4, pp.83-93, 1988.
DOI : 10.1109/2.53

X. Zeng and M. Singh, Approximation theory of fuzzy systems-MIMO case, IEEE Transactions on Fuzzy Systems, vol.3, issue.2, pp.219-235, 1995.
DOI : 10.1109/91.388175

J. Zhang and J. Morris, Recurrent neuro-fuzzy networks for nonlinear process modeling, IEEE Transactions on Neural Networks, vol.10, issue.2, pp.313-326, 1999.
DOI : 10.1109/72.750562

O. C. Zienkiewicz, The Finite Element Method in Engineering Science, 1967.