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[138] I Cloete and J Ludik Delta Training Strategies In IEEE World Congress on Computational Intelligence, Proceedings of the International Joint Conference on Neural Networks, volume 1, pages 295 298, 1994 [139] I Cloete and J Ludik Incremental Training Strategies In Proceedings of the International Conference on Artificial Neural Networks, volume 2, pages 743 746, 1994 [140] G Coath and SK Halgamuge A Comparison of Constraint-Handling Methods for The Application of Particle Swarm Optimization to Constrained Nonlinear Optimization Problems In Proceedings of the IEEE Congress on Evolutionary Computation, volume 4, pages 2419 2425, 2003 [141] HG Cobb An Investigation into The Use of Hypermutation as An Adaptive Operator in Genetic Algorithms having Continuous, Time-Dependent Nonstationary Environments Technical Report AIC-90-001, Naval Research Laboratory, Washington, DC, 1990 [142] JP Coelho, PB De Moura Oliveira, and J Boa Ventura Cunha Non-Linear Concentration Control System Design using A New Adaptive PSO In Proceedings of the 5th Portuguese Conference on Automatic Control, 2002 [143] JP Coelho, PM Oliveira, and JB Cunha Greenhouse Air Temperature Control using the Particle Swarm Optimisation Algorithm In Proceedings of the Fifteenth Triennial World Congress of the International Federation of Automatic Control, 2002 [144] CA Coello Coello Self-Adaptive Penalties for GA-Based Optimization In Proceedings of the IEEE Congress on Evolutionary Computation, volume 1, 1999 [145] CA Coello Coello and RL Becerra Constrained Optimization using an Evolutionary Programming-based Cultural Algorithm In IC Parmee, editor, Proceedings of the Fifth International Conference on Adaptive Computing in Design and Manufacture, volume 5, pages 317 328 Springer-Verlag, 2002 [146] CA Coello Coello and RL Becerra Evolutionary Multiobjective Optimization using a Cultural Algorithm In Proceedings of the IEEE Swarm Intelligence Symposium, pages 6 13, 2003 [147] CA Coello Coello and MS Lechuga MOPSO: A Proposal for Multiple Objective Particle Swarm Optimization In Proceedings of the IEEE Congress on Evolutionary Computation, volume 2, pages 1051 1056, 2002 [148] CA Coello Coello, G Toscano Pulido, and M Salazar Lechuga An Extension of Particle Swarm Optimization that can Handle Multiple Objectives In Workshop on Multiple Objective Metaheuristics, 2002 [149] CA Coello Coello, DA van Veldhuizen, and GB Lamont Evolutionary Algorithms for Solving Multi-Objective Problems Plenum US, 2002 [150] CA Coello Coello, DA Van Veldhuizen, and GB Lamont Evolutionary Algorithms for Solving Multi-Objective Problems Kluwer Academic Publishers, 2002 [151] D Cohn, L Atlas, and R Ladner Improving Generalization with Active Learning Machine Learning, 15:201 221, 1994 [152] D Cohn and G Tesauro Can Neural Networks do Better than the VapnikChervonenkis Bounds In R Lippmann, J Moody, and DS Touretzky, editors, Advances in Neural Information Processing Systems, volume 3, pages 911 917, 1991
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[153] DA Cohn Neural Network Exploration using Optimal Experiment Design Technical Report AI Memo No 1491, Arti cial Intelligence Laboratory, Massachusetts Institute of Technology, 1994 [154] DA Cohn, Z Ghahramani, and MI Jordan Active Learning with Statistical Models Journal of Artificial Intelligence Research, 4:129 145, 1996 [155] A Conradie, R Miikkulainen, and C Aldrich Adaptive Control Utilizing Neural Swarming In Proceedings of the Genetic and Evolutionary Computation Conference, pages 60 67, 2002 [156] J Conradie and AP Engelbrecht Training Bao Game-Playing Agents using Coevolutionary Particle Swarm Optimization In Proceedings of the IEEE Symposium on Computational Intelligence in Games, pages 67 74, 2006 [157] D Corne, M Dorigo, and F Glover New Ideas in Optimization McGraw-Hill, 1999 [158] M Cosnard, P Koiran, and H Paugam-Moisy Complexity Issues in Neural Network Computations In I Simon, editor, Proceedings of the First Latin American Symposium on Theoretical Informatics, Lecture Notes in Computer Science, volume 583, pages 530 543 Springer-Verlag, 1992 [159] L Costa and P Oliveira An Evolution Strategy for Multiobjective Optimization In Proceedings of the IEEE Congress on Evolutionary Computation, volume 1, pages 97 102, 2002 [160] M Cottrell, B Girard, Y Girard, M Mangeas, and C Muller SSM: A Statistical Stepwise Method for Weight Elimination In Proceedings of the International Conference on Artificial Neural Networks, volume 1, pages 681 684, 1994 [161] T Coudert, P Berruet, and J-L Philippe Integration of Recon guration in Transitic Systems: An Agent-Based Approach In Proceedings of the IEEE International Conference on Systems, Man and Cybernetics, volume 4, pages 4008 4014, 2003 [162] R Coulom Feedforward Neural Networks in Reinforcement Learning Applied to High-Dimensional Motor Control In N Cesa-Bianchi et al, editor, Lecture Notes in Artificial Intelligence, pages 403 413, Berlin Heidelberg, 2002 SpringerVerlag [163] GS Cowan and RG Reynolds Learning to Access the Quality of Genetic Programs using Cultural Algorithms In Proceedings of the IEEE Congress on Evolutionary Computation, volume 3, pages 1679 1686, 1999 [164] IL L pez Cruz, LG van Willigenburg, and G van Straten E cient Di erential o Evolution algorithms for multimodal optimal control problems Applied Soft Computing, 3(2):97 122, 2003 [165] IL L pez Cruz, LG van Willigenburg, and G van Straten Optimal Control of o Nitrate in Lettuce by a Hybrid Approach: Di erential Evolution and Adjustable Control Weight Gradient Algorithms Computers and Electronics in Agriculture, 40(1-3):179 197, 2003 [166] Y Le Cun, JS Denker, and SA Solla Optimal Brain Damage In D Touretzky, editor, Advances in Neural Information Processing Systems, volume 2, pages 598 605, 1990
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