By Michael Defoin Platel, Sebastien Verel, Manuel Clergue, Philippe Collard (auth.), Pierre Liardet, Pierre Collet, Cyril Fonlupt, Evelyne Lutton, Marc Schoenauer (eds.)
This e-book constitutes the completely refereed post-proceedings of the sixth overseas convention on synthetic Evolution, EA 2003, held in Marseilles, France in October 2003.
The 32 revised complete papers provided have been conscientiously chosen and more desirable in the course of rounds of reviewing and revision. The papers are prepared in topical sections on theoretical concerns, algorithmic concerns, purposes, implementation concerns, genetic programming, coevolution and agent structures, man made lifestyles, and mobile automata.
Read or Download Artificial Evolution: 6th International Conference, Evolution Artificielle, EA 2003, Marseilles, France, October 27-30, 2003, Revised Selected Papers PDF
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Additional info for Artificial Evolution: 6th International Conference, Evolution Artificielle, EA 2003, Marseilles, France, October 27-30, 2003, Revised Selected Papers
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Even Length Binary Sequence Families with Low Negaperiodic Autocorrelation, LNCS 2227 (2001), pp 200–210. 11. , A Hybrid Local Search Algorithm for Low-Autocorrelation Binary Sequences, Tech. Report TR-00-01, Dept. Comp. , National Univ. Ireland at Cork, pp. 14. 12. , Number Theory in Science and Communication, Springer, Berlin (1984).
3. , The merit factor of long low autocorrelation binary sequences , IEEE Trans. Inf. theory, IT-23 (1982) 43–51. 4. , The merit factor of Legendre sequences, IEEE Trans. Inf. theory, IT-29, 1983, 934-936. 5. , Würtz D. , Low Autocorrelation Binary Sequences: Exact Enumeration and Optimization by Evolutionary Strategies, Optimization, 23 (1992), Gordon & Breach Science Publish. S. , 369–384. 6. , The Merit Factor of Binary sequences. Difference Sets, Sequences and their Correlation Properties, A.
6. Evolution of the probability distribution for the outermost ply tribution for the innermost ply SHC, however, is unaffected by the problem’s hierarchical structure because it merely compares two neighboring points. Fig. 7 shows the two performance measures on the two problems. Both the number of evaluations to 98% of the maximum fitness and the number of evaluations until 80% reliability is achieved are lower for the vibration problem than for the Max problem. L. Grosset, R. T. Haftka 34 Fig.