This monograph presents examples of best practices when combining bioinspired algorithms with parallel architectures. The book includes recent work by leading researchers in the field and offers a map with the main paths already explored and new ways towards the future.<br>Parallel Architectures and
Parallel Architectures and Bioinspired Algorithms
✍ Scribed by Francisco Fernández de Vega (auth.), Francisco Fernández de Vega, José Ignacio Hidalgo Pérez, Juan Lanchares (eds.)
- Publisher
- Springer-Verlag Berlin Heidelberg
- Year
- 2012
- Tongue
- English
- Leaves
- 287
- Series
- Studies in Computational Intelligence 415
- Edition
- 1
- Category
- Library
No coin nor oath required. For personal study only.
✦ Synopsis
This monograph presents examples of best practices when combining bioinspired algorithms with parallel architectures. The book includes recent work by leading researchers in the field and offers a map with the main paths already explored and new ways towards the future.
Parallel Architectures and Bioinspired Algorithms will be of value to both specialists in Bioinspired Algorithms, Parallel and Distributed Computing, as well as computer science students trying to understand the present and the future of Parallel Architectures and Bioinspired Algorithms.
✦ Table of Contents
Front Matter....Pages 1-5
Introduction....Pages 1-6
Creating and Debugging Performance CUDA C....Pages 7-50
Optimizing Shape Design with Distributed Parallel Genetic Programming on GPUs....Pages 51-75
Characterizing Fault-Tolerance in Evolutionary Algorithms....Pages 77-99
Comparison of Frameworks for Parallel Multiobjective Evolutionary Optimization in Dynamic Problems....Pages 101-123
An Empirical Study of Parallel and Distributed Particle Swarm Optimization....Pages 125-150
The Generalized Island Model....Pages 151-169
Evolutionary Associative Memories through Genetic Programming....Pages 171-188
Parallel Architectures for Improving the Performance of a GA Based Trading System....Pages 189-218
A Knowledge-Based Operator for a Genetic Algorithm which Optimizes the Distribution of Sparse Matrix Data....Pages 219-241
Evolutive Approaches for Variable Selection Using a Non-parametric Noise Estimator....Pages 243-266
A Chemical Evolutionary Mechanism for Instantiating Service-Based Applications....Pages 267-286
Back Matter....Pages 0--1
✦ Subjects
Computational Intelligence; Artificial Intelligence (incl. Robotics)
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