Results 261 to 270 of about 46,925 (311)

Hyperinteractive Evolutionary Computation

IEEE Transactions on Evolutionary Computation, 2011
We propose hyperinteractive evolutionary computation (HIEC), a class of IEC in which the user actively chooses when and how each evolutionary operator is applied. To evaluate the benefits of HIEC, we conducted three human-subject experiments. The first two experiments showed that HIEC is associated with a more positive user experience and produced ...
Benjamin James Bush, Hiroki Sayama
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Computational complexity and evolutionary computation

Proceedings of the 9th annual conference companion on Genetic and evolutionary computation, 2007
Evolutionary algorithms and other nature-inspired search heuristics like ant colony optimization have been shown to be very successful when dealing with real-world applications or problems from combinatorial optimization. In recent years, analyses has shown that these general randomized search heuristics can be analyzed like "ordinary" randomized ...
Thomas Jansen 0001, Frank Neumann 0001
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Evolutionary computation

Nature Reviews Genetics, 2001
Evolution does not require DNA, or even living organisms. In computer science, the field known as 'evolutionary computation' uses evolution as an algorithmic tool, implementing random variation, reproduction and selection by altering and moving data within a computer.
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Evolutionary computation: an overview

Proceedings of IEEE International Conference on Evolutionary Computation, 2002
We 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, 2016
Evolutionary 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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Evolutionary computation

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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On Clustering in Evolutionary Computation

2006 IEEE International Conference on Evolutionary Computation, 2006
When 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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Computational Evolutionary Musicology

2007
The 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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Introduction to Evolutionary Computing

Evolutionary Computation, 2004
This 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 Perception

Perception, 2012
Marr 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 along
Donald D, Hoffman, Manish, Singh
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