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Evolutionary computation: an overview
Proceedings of IEEE International Conference on Evolutionary Computation, 2002We present an overview of the most important representatives of algorithms gleaned from natural evolution, so-called evolutionary algorithms. Evolution strategies, evolutionary programming, and genetic algorithms are summarized, with special emphasis on the principle of strategy parameter self-adaptation utilized by the first two algorithms to learn ...
Thomas Bäck, Hans-Paul Schwefel
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Evolutionary computation and cryptology
Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2016Evolutionary Computation (EC) has been used with great success on various real-world problems. One domain abundant with numerous difficult problems is cryptology. Cryptology can be divided into cryptography, that informally speaking considers methods how to ensure secrecy (but also authenticity, privacy, etc.), and cryptanalysis, that deals with ...
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Proceedings of the 12th annual conference companion on Genetic and evolutionary computation, 2007
The field of Evolutionary Computation has experienced tremendous growth over the past 20 years, resulting in a wide variety of evolutionary algorithms and applications. The result poses an interesting dilemma for many practitioners in the sense that, with such a wide variety of algorithms and approaches, it is often hard to se the relationships between
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The field of Evolutionary Computation has experienced tremendous growth over the past 20 years, resulting in a wide variety of evolutionary algorithms and applications. The result poses an interesting dilemma for many practitioners in the sense that, with such a wide variety of algorithms and approaches, it is often hard to se the relationships between
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Computational Evolutionary Perception
Perception, 2012Marr proposed that human vision constructs “a true description of what is there”. He argued that to understand human vision one must discover the features of the world it recovers and the constraints it uses in the process. Bayesian decision theory (BDT) is used in modern vision research as a probabilistic framework for understanding human vision ...
Donald D, Hoffman, Manish, Singh
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Evolutionary computation and games
IEEE Computational Intelligence Magazine, 2006Games provide competitive, dynamic environments that make ideal test beds for computational intelligence theories, architectures, and algorithms. Natural evolution can be considered to be a game in which the rewards for an organism that plays a good game of life are the propagation of its genetic material to its successors and its continued survival ...
Simon M. Lucas, Graham Kendall
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Introduction to Evolutionary Computing
Evolutionary Computation, 2004This book was written by its two authors with the explicit intention that it would become one of the standard text books on evolutionary computation, to rival ”the greats”, namely those of Goldberg (1989), Davis (1991), Michalewicz (1992-1996), Koza (1992), Back (1995), and Mitchell (1996) .
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Computational Evolutionary Musicology
2007The beginning of Chapter 2 offered a sensible definition of music as temporally organized sound. In the broader sense of this definition, one could arguably state that music is not uniquely human. A number of other animals also seem to have music of some sort. Complex vocalizations can be found in many birds (Marler and Slabbekoorn 2004), as well as in
Miranda, E., Todd, P.
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On Clustering in Evolutionary Computation
2006 IEEE International Conference on Evolutionary Computation, 2006When the fitness landscape exhibits a multi-modal property, clustering plays a key role in the evolutionary computation, because clusters explicitly or implicitly denote optima present. Correct clusters result in effective and efficient evolution. In this paper, a novel clustering strategy, called Recursive Middling (RM), is proposed.
Jie Yao, Nawwaf Kharma, Yu-Qing Zhu
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Representation in Evolutionary Computation
2012The representation of a problem for evolutionary computation is the choice of the data structure used for solutions and the variation operators that act upon that data structure. For a difficult problem, choosing a good representation can have an enormous impact on the performance of the evolutionary computation system.
Daniel A. Ashlock +2 more
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Evolutionary computing in robotics
Artificial Life and Robotics, 2002Intelligent systems are required in knowledge engineering, computer science, mechatronics, and robotics. This article discusses machine (system) intelligence from the viewpoints of the learning and adaptation of living things. We then introduce computational intelligence, including neural networks, fuzzy systems, and genetic algorithms, and end with a ...
Toshio Fukuda, Yasuhisa Hasegawa
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