Results 281 to 290 of about 6,048,895 (335)
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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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A perspective on evolutionary computation
1995During the last three decades there has been a growing interest in algorithms which rely on analogies to natural processes. The emergence of massively parallel computers made these algorithms of practical interest. The best known algorithms in this class include evolutionary programming, genetic algorithms, evolution strategies, simulated annealing ...
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Theoretical and Applied Climatology, 2021
Mohd Khairul Idlan Muhammad +5 more
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Mohd Khairul Idlan Muhammad +5 more
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Soft Computing - A Fusion of Foundations, Methodologies and Applications, 1998
This paper elaborates on a new paradigm of computing embracing fuzzy sets and evolutionary methods (specially genetic algorithms). We discuss conceptual and algorithmic enhancements to the individual methods. Fuzzy sets are geared toward granular information processing. Evolutionary computing are population-based optimization methods.
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This paper elaborates on a new paradigm of computing embracing fuzzy sets and evolutionary methods (specially genetic algorithms). We discuss conceptual and algorithmic enhancements to the individual methods. Fuzzy sets are geared toward granular information processing. Evolutionary computing are population-based optimization methods.
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Evolutionary Computation and Games
Proceedings of the 2016 on Genetic and Evolutionary Computation Conference Companion, 2016In recent years, the field of Computational Intelligence and Games (CIG) has enjoyed rapid progress and a sharp rise in popularity. In this field, algorithms from across the computational intelligence spectrum are tested on benchmarks based on e.g. board games and video games, and new CI-based solutions are developed for problems in game development ...
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Evolutionary Computing and Mobile Sustainable Networks
Lecture Notes on Data Engineering and Communications Technologies, 2021semanticscholar +1 more source
International Journal for Numerical Methods in Engineering
Quantum computing platforms offer unique advantages—such as inherent parallelism and efficient handling of large‐scale computations—that unlock novel solutions for complex structural design challenges.
Zheng-Huan Wang, Xiao-Jun Wang
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Quantum computing platforms offer unique advantages—such as inherent parallelism and efficient handling of large‐scale computations—that unlock novel solutions for complex structural design challenges.
Zheng-Huan Wang, Xiao-Jun Wang
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Evolutionary computation and games
Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion, 2020Julian Togelius +2 more
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