Experimental Research in Evolutionary Computation
The New Experimentalism (Natural Computing Series)
By Thomas Bartz-Beielstein
"Experimental Research in Evolutionary Computation" is published by Springer in April 28, 2006 - Berlin ; New York, it has 214 pages and the language of the book is English.
“Experimental Research in Evolutionary Computation” Metadata:
- Title: ➤ Experimental Research in Evolutionary Computation
- Author: Thomas Bartz-Beielstein
- Language: English
- Number of Pages: 214
- Publisher: Springer
- Publish Date: April 28, 2006
- Publish Location: Berlin ; New York
“Experimental Research in Evolutionary Computation” Subjects and Themes:
- Subjects: ➤ Evolutionary programming (Computer science) - Methodology - Systeemtheorie - Computação evolutiva (pesquisa;metodologia) - Computação bioinspirada - Evolutionary computation - Research - Computer science - Information theory - Artificial intelligence - Computer simulation - Mathematical optimization - Engineering mathematics - Theory of Computation - Artificial Intelligence (incl. Robotics) - Simulation and Modeling - Computer Applications - Optimization - Appl.Mathematics/Computational Methods of Engineering
Edition Specifications:
- Format: Hardcover
- Weight: 15.2 ounces
- Dimensions: 9.4 x 6.2 x 0.2 inches
Edition Identifiers:
- The Open Library ID: OL9056270M - OL9032175W
- Online Computer Library Center (OCLC) ID: 68804868
- Library of Congress Control Number (LCCN): 2006922082
- ISBN-13: 9783540320265
- ISBN-10: 3540320261
- All ISBNs: 3540320261 - 9783540320265
AI-generated Review of “Experimental Research in Evolutionary Computation”:
"Experimental Research in Evolutionary Computation" Description:
The Open Library:
Experimentation is necessary - a purely theoretical approach is not reasonable. The new experimentalism, a development in the modern philosophy of science, considers that an experiment can have a life of its own. It provides a statistical methodology to learn from experiments, where the experimenter should distinguish between statistical significance and scientific meaning. This book introduces the new experimentalism in evolutionary computation, providing tools to understand algorithms and programs and their interaction with optimization problems. The book develops and applies statistical techniques to analyze and compare modern search heuristics such as evolutionary algorithms and particle swarm optimization. Treating optimization runs as experiments, the author offers methods for solving complex real-world problems that involve optimization via simulation, and he describes successful applications in engineering and industrial control projects. The book bridges the gap between theory and experiment by providing a self-contained experimental methodology and many examples, so it is suitable for practitioners and researchers and also for lecturers and students. It summarizes results from the author's consulting to industry and his experience teaching university courses and conducting tutorials at international conferences. The book will be supported online with downloads and exercises.
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