Massively Parallel Evolutionary Computation on GPGPUs by Shigeyoshi Tsutsui
Recent advances in general-purpose computing on graphics processing units (GPGPU) have opened up the possibility for parallel evolutionary algorithms. This book details this exciting new approach, with emphasis on solving practical problems.-
Robot Evolution
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An Introduction to Metaheuristics for Optimization
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Deep Neural Evolution
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Lectures on Intelligent Systems
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Deep Statistical Comparison for Meta-heuristic Stochastic Optimization Algorithms
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Coevolutionary Computation and Its Applications
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Visions of DNA Nanotechnology at 40 for the Next 40
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Cartesian Genetic Programming
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Bioinspired Computation in Combinatorial Optimization
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Self-organising Software
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Swarm Intelligence
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Evolution as Computation
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Algorithmic Bioprocesses
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General-Purpose Optimization Through Information Maximization
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Nature Inspired Optimisation for Delivery Problems
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Experimental Research in Evolutionary Computation
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Hyper-Heuristics: Theory and Applications
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Modelling in Molecular Biology
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Advances in Metaheuristics for Hard Optimization
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Foraging-Inspired Optimisation Algorithms
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Mobility in Process Calculi and Natural Computing
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Automating the Design of Data Mining Algorithms
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Contemporary Evolution Strategies
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Theory and Principled Methods for the Design of Metaheuristics
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Discrete and Topological Models in Molecular Biology
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Multimodal Optimization by Means of Evolutionary Algorithms
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Computation in Living Cells
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Sensitivity Analysis for Neural Networks
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Reservoir Computing
Prof. Shigeyoshi Tsutsui received his B.Eng. and M.Eng. in electrical engineering in 1967 and 1969 respectively from Osaka City University, and he received his Ph.D. in 1985 from Osaka Prefecture University. From 1969 to 1986 he worked in Hitachi's Central Research Laboratories and Systems Development Laboratories. He joined the staff of Hannan University in 1987, where he is currently a full professor. His reseach interests include computer architectures, information and business science, artificial intelligence, and evolutionary computing, in particular applying genetic algorithms to difficult, multimodal problems.
Prof. Pierre Collet received his master's degree in operating systems from Université de Paris VI in 1990, and his Ph.D. from Université Paris-Sud (Orsay) in 1997, on the topic of computer-aided surgery through virtual reality. From 2000 to 2003 he was a researcher in the Artificial Evolution and Learning team of the Center of Applied Mathematics (CMAP) of École Polytechnique. He joined the Université du Littoral Côte d'Opale in Calais in 2003 as an assistant professor, and defended his habilitation thesis in 2004. In 2007 he became a full professor in the Image Sciences, Computer Sciences and Remote Sensing Laboratory (LSIIT) in Strasbourg, where he led the Theoretical Bionformatics, Data Mining and Stochastic Optimization (BFO) team until December 2012. Since 2011, he has been the head of the Dept. of Computer Science of the Université de Strasbourg, and since 2013 he has led the Strasbourg Complex Systems Digital Campus. His research concentrates on the optimization of complex problems using evolutionary computing, nature-inspired stochastic algorithms, and complex systems, and in particular their implementation on massively parallel hardware, with applications in collaborative work, cellular automata, biomedical devices, chemistry, control, and e-learning.
| SKU | Unavailable |
| ISBN 13 | 9783662513453 |
| ISBN 10 | 3662513455 |
| Title | Massively Parallel Evolutionary Computation on GPGPUs |
| Author | Shigeyoshi Tsutsui |
| Series | Natural Computing Series |
| Condition | Unavailable |
| Binding Type | Paperback |
| Publisher | Springer |
| Year published | 2016-08-23 |
| Number of pages | 453 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |