Ebook: Parallel Problem Solving from Nature — PPSN III: International Conference on Evolutionary Computation The Third Conference on Parallel Problem Solving from Nature Jerusalem, Israel, October 9–14, 1994 Proceedings
Author: Darrell Whitley V. Scott Gordon (auth.) Yuval Davidor Hans-Paul Schwefel Reinhard Männer (eds.)
- Genre: Mathematics // Computational Mathematics
- Tags: Processor Architectures, Programming Techniques, Computation by Abstract Devices, Algorithm Analysis and Problem Complexity, Artificial Intelligence (incl. Robotics), Mathematical Biology in General
- Series: Lecture Notes in Computer Science 866
- Year: 1994
- Publisher: Springer-Verlag Berlin Heidelberg
- Edition: 1
- Language: English
- djvu
This volume comprises the 61 revised refereed papers accepted for presentation at the ICEC/PPSN III conferences held jointly in Jerusalem, Israel in October 1994.
With the appearance of more and more powerful computers, there is increased interest in algorithms relying upon analogies to natural processes. This book presents a wealth of new theoretical and experimental results on artificial problem solving by applying evolutionary computation metaphors, including evolution strategies, evolutionary programming, genetic algorithms, genetic programming, and classifier systems. Topics such as simulated annealing, immune networks, neural networks, fuzzy systems, and complex, real-world optimization problems are also treated.
This volume comprises the 61 revised refereed papers accepted for presentation at the ICEC/PPSN III conferences held jointly in Jerusalem, Israel in October 1994. With the appearance of more and more powerful computers, there is increased interest in algorithms relying upon analogies to natural processes. This book presents a wealth of new theoretical and experimental results on artificial problem solving by applying evolutionary computation metaphors, including evolution strategies, evolutionary programming, genetic algorithms, genetic programming, and classifier systems. Topics such as simulated annealing, immune networks, neural networks, fuzzy systems, and complex, real-world optimization problems are also treated.
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