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

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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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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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.
Content:
Front Matter....Pages -
Lamarckian evolution, the Baldwin effect and function optimization....Pages 5-15
Control of parallel population dynamics by social-like behavior of GA-individuals....Pages 16-25
Studying genotype-phenotype interactions: A model of the evolution of the cell regulation network....Pages 26-35
A diploid genetic algorithm for preserving population diversity — Pseudo-Meiosis GA....Pages 36-45
Co-evolutionary constraint satisfaction....Pages 46-55
Advanced correlation analysis of operators for the traveling salesman problem....Pages 57-67
Genetic algorithms with multi-parent recombination....Pages 68-77
On the mean convergence time of evolutionary algorithms without selection and mutation....Pages 78-87
Estimating the heritability by decomposing the genetic variance....Pages 88-97
Analyzing hyperplane synthesis in genetic algorithms using clustered schemata....Pages 98-107
Convergence models of genetic algorithm selection schemes....Pages 108-118
Optimal population size under constant computation cost....Pages 119-129
An evolutionary algorithm for integer programming....Pages 130-138
Long path problems....Pages 139-148
Evolution strategies on noisy functions how to improve convergence properties....Pages 149-158
Selection schemes with spatial isolation for genetic optimization....Pages 159-168
A modified edge recombination operator for the Travelling Salesman Problem....Pages 169-179
Step-size adaptation based on non-local use of selection information....Pages 180-188
Strategy adaptation by competing subpopulations....Pages 189-198
Controlling crossover through inductive learning....Pages 199-208
Derivative operators for preference predicate evolution....Pages 209-218
Adaptive crossover using automata....Pages 219-228
Controlling dynamics of GA through filtered evaluation function....Pages 229-238
A cooperative coevolutionary approach to function optimization....Pages 239-248
A fuzzy classifier system using the Pittsburgh approach....Pages 249-257
Q-learning in Evolutionary Rule Based Systems....Pages 259-269
On the complexity of learning in classifier systems....Pages 270-279
A representation scheme to perform program induction in a canonical genetic algorithm....Pages 280-289
Genetic Programming with local hill-climbing....Pages 291-301
Dynamic training subset selection for supervised learning in Genetic Programming....Pages 302-311
Genotype-phenotype-mapping and neutral variation — A case study in Genetic Programming....Pages 312-321
Genetic L-System Programming....Pages 322-332
A genetic algorithm discovers particle-based computation in cellular automata....Pages 333-343
Simulation of exaptive behaviour....Pages 344-353
Artificial spacing patterns in a network of interacting celloids....Pages 354-364
Diffuse pattern learning with Fuzzy ARTMAP and PASS....Pages 365-374
Different learning algorithms for Neural Networks — A comparative study....Pages 375-385
Program search with a hierarchical variable length representation: Genetic Programming, simulated annealing and hill climbing....Pages 386-396
Problem-independent Parallel Simulated Annealing using selection and migration....Pages 397-406
Parallel optimization of evolutionary algorithms....Pages 407-417
Parallel simulated annealing and genetic algorithms: A space of hybrid methods....Pages 418-427
ENZO-M — A hybrid approach for optimizing neural networks by evolution and learning....Pages 428-438
Genetic lander: An experiment in accurate neuro-genetic control....Pages 439-451
Effects of Occam's razor in evolving Sigma-Pi neural nets....Pages 452-461
Designing neural networks by adaptively building blocks in cascades....Pages 462-471
Hybrid adaptive heuristic critic architectures for learning in mazes with continuous search spaces....Pages 472-481
Mutation operators for structure evolution of neural networks....Pages 482-491
Implementation of standard genetic algorithm on MIMD machines....Pages 492-501
Loosely coupled distributed genetic algorithms....Pages 503-513
Applying Evolvable Hardware to autonomous agents....Pages 514-523
Genetic Algorithms on LAN-message passing architectures using PVM: Application to the Routing problem....Pages 524-533
Genetic algorithm based design optimization of CMOS VLSI circuits....Pages 534-543
Improving evolutionary timetabling with delta evaluation and directed mutation....Pages 545-555
Genetic improvement of railway timetables....Pages 556-565
Using a genetic algorithm to search for the representational bias of a collective reinforcement learner....Pages 566-575
An evolutionary algorithm for the routing of multi-chip modules....Pages 576-587
System design under uncertainty: Evolutionary optimization of the Gravity Probe-B spacecraft....Pages 588-597
Soft selection in D-optimal designs....Pages 598-607
The weighted graph bi-partitioning problem: A look at GA performance....Pages 608-616
Back Matter....Pages 617-625
RPL2: A language and parallel framework for evolutionary computing....Pages -
....Pages 627-637