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Evolutionary Algorithms, Swarm Dynamics and Complex Networks
Engleski
249 b
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This book puts forward novel ideas, advancing evolutionary dynamics to address new phenomena and new topics, even the dynamics of equivalent social networks. It demonstrates that evolutionary algorithms can be understood just like dynamical systems with feedback. Evolutionary algorithms constitute a class of well-known algorithms that are based on the Darwinian theory of evolution and Mendelian theory of heritage. They are partly based on random and partly on deterministic principles. Recently, the study of evolutionary dynamics has focused not only on the traditional investigations but also on understanding and analyzing new principles, the goal being to hone and harness their qualities and performance for more effective real-world applications. Thus, at least in theory, all engineering control methods can be applied. All of these ideas are illustrated and discussed in the book's respective chapters. All the chapter authors are originators of the ideas mentioned above and researchers intensively engaged in evolutionary algorithms, chaotic dynamics and complex networks, and offer readers essential insights into the latest scientific research on these subjects.
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