http://de.evo-art.org/index.php?action=history&feed=atom&title=A_Lamarckian_Evolution_Strategy_for_Genetic_Algorithms 2026-05-17T23:00:08Z Versionsgeschichte dieser Seite in de_evolutionary_art_org MediaWiki 1.27.4 http://de.evo-art.org/index.php?title=A_Lamarckian_Evolution_Strategy_for_Genetic_Algorithms&diff=3328&oldid=prev 2015-01-14T11:10:16Z

<p>Die Seite wurde neu angelegt: „== Reference == <a href="/index.php?title=Brian_J._Ross" title="Brian J. Ross">Brian J. Ross</a>: <a href="/index.php?title=A_Lamarckian_Evolution_Strategy_for_Genetic_Algorithms" title="A Lamarckian Evolution Strategy for Genetic Algorithms">A Lamarckian Evolution Strategy for Genetic Algorithms</a>. In: L. Chambers (ed.): Practical Handbook of Genetic Algorithms …“</p> <p><b>Neue Seite</b></p><div>== Reference ==<br /> [[Brian J. Ross]]: [[A Lamarckian Evolution Strategy for Genetic Algorithms]]. In: L. Chambers (ed.): Practical Handbook of Genetic Algorithms (vol.3), CRC Press, 1999, pp. 1-16. <br /> <br /> == DOI ==<br /> <br /> == Abstract ==<br /> A Prolog implementation of a simple Lamarckian evolution module for<br /> genetic algorithms is discussed. Lamarckian evolution posits that<br /> characteristics acquired during a phenotype&#039;s lifetime may be inherited by<br /> offspring. Although largely dismissed as a viable evolutionary theory for<br /> natural systems, Lamarckian evolution has proven effective within computer<br /> applications. The strengths of the implementation discussed here are its<br /> speed and simplicity -- the latter promoting extensibility and specialization to<br /> particular applications.<br /> <br /> == Extended Abstract ==<br /> <br /> == Bibtex == <br /> <br /> == Used References ==<br /> Ackley, D.H. and Littman, M.L. 1994. &quot;A Case for Lamarckian Evolution&quot;.<br /> Artificial Life III, Ed. C.G. Langton, Addison-Wesley.<br /> <br /> Back, T. 1992. “Self-Adaptation in Genetic Algorithms”. Proc. 1st ECAI, Dec<br /> 1991, MIT Press.<br /> <br /> Cochrane, E. 1997. &quot;Viva Lamarck: A Brief History of the Inheritance of<br /> Acquired Characteristics&quot;. [http://www.ames.net/aeon/].<br /> <br /> Dawkins, R. 1996. The Blind Watchmaker. Norton.<br /> <br /> Goldberg, D.E. 1989. Genetic Algorithms in Search, Optimization and<br /> Machine Learning. Addison-Wesley.<br /> <br /> Gould, S.J. 1980. The Panda&#039;s Thumb. New York: Norton.<br /> <br /> Grefenstette, J. J. 1986. “Optimization of control parameters for genetic<br /> algorithms”. IEEE Transactions on Systems, Man and Cybernetics, 16(1):122-<br /> 128.<br /> <br /> Grefenstette, J.J. 1991. &quot;Lamarckian Learning in Multi-agent Environments&quot;.<br /> Proc. 4th Intl. Conference on Genetic Algorithms, Morgan Kaufman.<br /> <br /> Hart, W.E. and Belew, R.K. 1996. &quot;Optimization with Genetic Algorithm<br /> Hybrids that Use Local Search&quot;. In Adaptive Individuals in Evolving<br /> Populations. Ed. R.K. Belew and M. Mitchell, Addison-Wesley.<br /> <br /> Li, Y., Tan, K.C., and Gong, M. 1996. &quot;Model Reduction in Control Systems by<br /> Means of Global Structure Evolution and Local Parameter Learning&quot;.<br /> Evolutionary Algorithms in Engineering Applications, ed. D. Dasgupta and Z.<br /> Michalewicz, Springer Verlag.<br /> <br /> Mitchell, M. 1996. An Introduction to Genetic Algorithms. MIT Press.<br /> <br /> Tamaki, H., Kita, H., Shimizu, N., Maekawa, K., and Nishikawa, Y. 1994. &quot;A<br /> Comparison Study of Genetic Codings for the Traveling Salesman Problem&quot;.<br /> 1st IEEE Conference on Evolutionary Computation, June 1994.<br /> <br /> Winston, P.H. 1992. Artificial Intelligence (3e). Addison-Wesley.<br /> <br /> <br /> == Links ==<br /> === Full Text === <br /> http://www.cosc.brocku.ca/~bross/research/Lamarck.ps<br /> <br /> [[intern file]]<br /> <br /> === Sonstige Links ===</div>

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