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[261] L Fletcher, V Katkovnik, FE Ste ens, and AP Engelbrecht Optimizing the Number of Hidden Nodes of a Feedforward Arti cial Neural Network In IEEE World Congress on Computational Intelligence, Proceedings of the International Joint Conference on Neural Networks, pages 1608 1612, 1998 [262] R Fletcher Practical Methods of Optimization John Wiley & Sons, 1987 [263] CA Floudas and PM Pardalos Recent Advances in Global Optimization Princeton Series in Computer Science, Princeton University Press, 1991 [264] TC Fogarty Varying the Probability of Mutation in the Genetic Algorithm In JD Scha er, editor, Proceedings of the Third International Conference on Genetic Algorithms, pages 104 109, San Mateo, CA, 1989 Morgan Kaufmann [265] DB Fogel System Identification through Simulated Evolution: A Machine Learning Approach to Modeling Ginn Press, Needham Heights, MA, 1991 [266] DB Fogel Evolving Artificial Intelligence PhD thesis, University of California, 1992 [267] DB Fogel Applying Fogel and Burgin s Competitive Goal-Seeking through Evolutionary Programming to Coordination, Trust, and Bargaining Games In Proceedings of the IEEE Congress on Evolutionary Computation, volume 2, pages 1210 1216, 2000 [268] DB Fogel Blondie24: Playing at the edge of AI Morgan Kaufmann, 2001 [269] DB Fogel, GB Fogel, and K Ohkura Multiple-Vector Self-Adaptation in Evolutionary Algorithms BioSystems, 61(2-3):155 162, 2001 [270] DB Fogel and LJ Fogel Optimal Routing of Multiple Autonomous Underwater Vehicles through Evolutionary Programming In Proceedings of the Symposium on Autonomous Underwater Vehicle Technology, pages 44 47, 1990 [271] DB Fogel, LJ Fogel, and JW Atmar Meta-Evolutionary Programming In Proceedings of the Twenty-Fifth Conference on Signals, Systems and Computers, volume 1, pages 540 545, 1991 [272] DB Fogel, LJ Fogel, and VW Porto Evolutionary Programming for Training Neural Networks In Proceedings of the IEEE International Joint Conference on Neural Networks, volume 1, pages 601 605, 1990 [273] DB Fogel, TJ Hays, and DR Johnson A Platform for Evolving Characters in Competitive Games In Proceedings of the IEEE Congress on Evolutionary Computation, volume 2, pages 1420 1426, 2004 [274] GB Fogel, GW Greenwood, and K Chellapilla Evolutionary Computation with Extinction: Experiments and Analysis In Proceedings of the IEEE Congress on Evolutionary Computation, volume 2, pages 1415 1420, 2000 [275] LJ Fogel Autonomous Automata Industrial Research, 4:14 19, 1962 [276] LJ Fogel On the Organization of Intellect PhD thesis, University of California, Los Angeles, 1964 [277] LJ Fogel, PJ Angeline, and DB Fogel An Evolutionary Programming Approach to Self-Adaptation on Finite State Machines In J McDonnell, R Reynolds, and DB Fogel, editors, Proceedings of the Fourth Annual Conference on Evolutionary Programming, pages 355 365 MIT Press, 1995 [278] LJ Fogel, A Owens, and M Walsh Artificial Intelligence through Simulated Evolution John Wiley & Sons, 1966
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[279] S Forrest and S Hofmeyr Immunology as Information Processing In LA Segel and I Cohen, editors, Design Principles for the Immune System and Other Distributed Autonomous Systems Oxford University Press, Santa Fe Institute Studies in the Sciences of Complexity New York, 2001 [280] S Forrest, S Hofmeyr, and A Somayaji Computer Immunology Communications of the ACM, 40(10):88 96, 1997 [281] S Forrest, AS Perelson, L Allen, and R Cherukuri Self-Nonself Discrimination in a Computer In Proceedings of the IEEE Symposium on Research in Security and Privacy, pages 202 212, 1994 [282] O Fournier, P Lopez, and J-D Lan Sun Luk Cyclic Scheduling Following the Social Behavior of Ant Colonies In Proceedings of the IEEE International Conference on Systems, Man and Cybernetics, volume 3, page 5, October 2002 [283] N Franken PSO-Based Coevolutionary Game Learning Master s thesis, Department of Computer Science, University of Pretoria, 2004 [284] N Franken and AP Engelbrecht Comparing PSO Structures to Learn the Game of Checkers from Zero Knowledge In Proceedings of the IEEE Congress on Evolutionary Computation, pages 234 241, 2003 [285] N Franken and AP Engelbrecht PSO Approaches to Co-Evolve IPD Strategies In Proceedings of the IEEE Congress on Evolutionary Computation, pages 356 363, 2004 [286] N Franken and AP Engelbrecht Particle Swarm Optimisation Approaches to Co-evolve Strategies for the Iterated Prisoner s Dilemma IEEE Transactions on Evolutionary Computation, 9(6):562 579, 2005 [287] B Franklin and M Bergerman Cultural Algorithms: Concepts and Experiments In Proceedings of the IEEE Congress on Evolutionary Computation, volume 2, pages 1245 1251, 2000 [288] AS Fraser Simulation of Genetic Systems by Automatic Digital Computers I: Introduction Australian Journal of Biological Science, 10:484 491, 1957 [289] AS Fraser Simulation of Genetic Systems by Automatic Digital Computers II: E ects of Linkage on Rates of Advance Under Selection Australian Journal of Biological Science, 10:492 499, 1957 [290] Y Freund and RE Schapire A Short Introduction to Boosting Journal of Japanese Society for Artificial Intelligence, 14(5):771 780, 1999 [291] B Fritzke Incremental Learning of Local Linear Mappings In Proceedings of the International Conference on Artificial Neural Networks, pages 217 222, 1995 [292] O Fujita Optimization of the Hidden Unit Function in Feedforward Neural Networks Neural Networks, 5:755 764, 1992 [293] T Fukuda and N Kubota Learning, Adaptation and Evolution of Intelligent Robotic System In Proceedings of the IEEE International Symposium on Intelligent Control, pages 2 7, 1998 [294] T Fukuda, K Mori, and M Tsukiyama Parallel Search for Multi-Modal Function Optimization with Diversity and Learning of Immune Algorithm In D Dasgupta, editor, Artificial Immune Systems and their Applications, pages 210 220 Springer, 1998
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