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Parallel Problem Solving from Nature — PPSN IV

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Table of Contents

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    Book Overview
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    Chapter 964 Computational brittleness and the evolution of computer viruses
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    Chapter 965 Evolutionary computing in multi-agent environments: Speciation and symbiogenesis
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    Chapter 966 Evolution strategies with subjective selection
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    Chapter 967 Emergent cooperation for multiple agents using genetic programming
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    Chapter 968 Evolution programs evolved
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    Chapter 969 Encoding scheme issues for open-ended artificial evolution
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    Chapter 970 Hardware evolution at function level
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    Chapter 971 Coevolutionary life-time learning
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    Chapter 972 Genetic programs and co-evolution
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    Chapter 973 Self-assemblage of gene nets in evolution via recruiting of new netters
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    Chapter 974 A survey of intron research in genetics
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    Chapter 975 Analytical and numerical investigations of evolutionary algorithms in continuous spaces
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    Chapter 976 On the asymptotic behavior of multirecombinant Evolution Strategies
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    Chapter 977 Are long path problems hard for genetic algorithms?
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    Chapter 978 Random tree generation for genetic programming
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    Chapter 979 Implicit formae in genetic algorithms
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    Chapter 980 A probabilistic database approach to the analysis of genetic algorithms
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    Chapter 981 Mean field analysis of tournament selection on a random manifold
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    Chapter 982 From recombination of genes to the estimation of distributions I. Binary parameters
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    Chapter 983 From recombination of genes to the estimation of distributions II. Continuous parameters
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    Chapter 984 Searching in the presence of noise
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    Chapter 985 The density of states — A measure of the difficulty of optimisation problems
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    Chapter 986 On interactive evolutionary algorithms and stochastic mealy automata
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    Chapter 987 The influence of different coding schemes on the computational complexity of genetic algorithms in function optimization
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    Chapter 988 An analysis of the effects of neighborhood size and shape on local selection algorithms
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    Chapter 989 Evolutionary computation at the edge of feasibility
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    Chapter 990 Dimensional analysis of allele-wise mixing revisited
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    Chapter 991 Gaussian diffusion in a simple genetic algorithm
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    Chapter 992 Erroneous truncation selection — A breeder's decision making perspective
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    Chapter 993 New crossover methods for sequencing problems
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    Chapter 994 The effect of extensive use of the mutation operator on generalization in genetic programming using sparse data sets
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    Chapter 995 On permutation representations for scheduling problems
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    Chapter 996 Multi-parent's niche: N-ary crossovers on NK-landscapes
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    Chapter 997 A preliminary investigation into directed mutations in evolutionary algorithms
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    Chapter 998 Heuristic crossovers for real-coded genetic algorithms based on fuzzy connectives
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    Chapter 999 Are evolutionary algorithms improved by large mutations?
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    Chapter 1000 Mutation by imitation in boolean evolution strategies
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    Chapter 1001 Formal algorithms + formal representations =search strategies
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    Chapter 1002 A genetic algorithm with variable range of local search for tracking changing environments
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    Chapter 1003 An Evolution Strategy with adaptation of the step sizes by a variance function
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    Chapter 1004 Every niching method has its niche: Fitness sharing and implicit sharing compared
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    Chapter 1005 Effects of isolation in a distributed population genetic algorithm
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    Chapter 1006 Self-adaptive genetic algorithm for numeric functions
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    Chapter 1007 Niche search: An evolutionary algorithm for global optimisation
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    Chapter 1008 Adaptively parameterised evolutionary systems: Self adaptive recombination and mutation in a genetic algorithm
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    Chapter 1009 Obtaining multiple distinct solutions with genetic algorithm niching methods
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    Chapter 1010 Cost Based Operator Rate Adaptation: An investigation
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    Chapter 1011 Genetic algorithms and relational landscapes
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    Chapter 1012 IOGA: An instance-oriented genetic algorithm
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    Chapter 1013 Explicit filtering of building blocks for genetic algorithms
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    Chapter 1014 Multi-objective optimization by means of the thermodynamical genetic algorithm
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    Chapter 1015 Adaptation to a changing environment by means of the thermodynamical genetic algorithm
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    Chapter 1016 The development of a dual-agent strategy for efficient search across whole system engineering design hierarchies
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    Chapter 1017 A parallel cellular genetic algorithm used in finite element simulation
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    Chapter 1018 A robust solution searching scheme in genetic search
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    Chapter 1019 Solving MasterMind using GAs and simulated annealing: A case of dynamic constraint optimization
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    Chapter 1020 Evolving compact solutions in genetic programming: A case study
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    Chapter 1021 Climbing up NP-hard hills
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    Chapter 1022 On the performance assessment and comparison of stochastic multiobjective optimizers
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    Chapter 1023 Paginating the generalized newspapers — A comparison of simulated annealing and a heuristic method
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    Chapter 1024 A comparison of optimization techniques for integrated manufacturing planning and scheduling
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    Chapter 1025 A comparison of search techniques on a wing-box optimisation problem
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    Chapter 1026 A comparative study of evolutionary algorithms for on-line parameter tracking
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    Chapter 1027 Modeling urban growth by cellular automata
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    Chapter 1028 Democratic optimization for discrete and continuous systems
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    Chapter 1029 A study of some properties of Ant-Q
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    Chapter 1030 Immunoid: An immunological approach to decentralized behavior arbitration of autonomous mobile robots
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    Chapter 1031 Parallelizable evolutionary dynamics principles for solving the maximum clique problem
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    Chapter 1032 Significance of locality and selection pressure in the grand deluge evolutionary algorithm
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    Chapter 1033 Parallel computing with DNA: Toward the anti-universal machine
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    Chapter 1034 Tackling the “curse of dimensionality” of radial basis functional neural networks using a genetic algorithm
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    Chapter 1035 A Three-stage method for designing Genetic Fuzzy Systems by learning from examples
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    Chapter 1036 Learning heuristics for OBDD minimization by Evolutionary Algorithms
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    Chapter 1037 Improving the generalization performance of multi-layer-perceptrons with population-based incremental learning
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    Chapter 1038 Robust GP in robot learning
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    Chapter 1039 A pattern recognition system using evolvable hardware
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    Chapter 1040 Topology design of feedforward neural networks by genetic algorithms
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    Chapter 1041 An evolution strategy for on-line optimisation of dynamic objective functions
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    Chapter 1042 Exploiting competing subpopulations for automatic generation of test sequences for digital circuits
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    Chapter 1043 Constraint handling in evolutionary search: A case study of the frequency assignment
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    Chapter 1044 An application of genetic algorithms and neural networks to scheduling power generating systems
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    Chapter 1045 Evolutionary algorithms for the calculation of electron distributions in Si-MOSFETs
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    Chapter 1046 Refueling of a nuclear power plant: Comparison of a naive and a specialized mutation operator
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    Chapter 1047 Genetic algorithms applied to the physical design of VLSI circuits: A survey
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    Chapter 1048 Stochastic methods for transistor size optimization of CMOS VLSI circuits
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    Chapter 1049 An adaptive parallel Genetic Algorithm for VLSI-layout optimization
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    Chapter 1050 Genetic algorithms for protocol validation
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    Chapter 1051 Constraint handling for the fault coverage code generation problem: An inductive evolutionary approach
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    Chapter 1052 New genetic local search operators for the traveling salesman problem
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    Chapter 1053 An evolutionary approach to hardware/software partitioning
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    Chapter 1054 Evolutionary Air Traffic Flow Management for large 3D-problems
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    Chapter 1055 Genetic-based dynamic load balancing: Implementation and evaluation
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    Chapter 1056 Production scheduling with genetic algorithms and simulation
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    Chapter 1057 Network optimization using evolutionary strategies
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    Chapter 1058 Co-evolving parallel random number generators
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    Chapter 1059 Scheduling by genetic local search with multi-step crossover
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    Chapter 1060 Finding the conformation of organic molecules with genetic algorithms
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    Chapter 1061 Investigating a Parallel Breeder Genetic Algorithm on the inverse Aerodynamic design
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    Chapter 1062 An evolutionary design for f -θ lenses
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    Chapter 1063 Optimization of heat exchanger networks by means of evolution strategies
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    Chapter 1064 Industrial plant pipe-route optimisation with genetic algorithms
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    Chapter 1065 An evolutionary algorithm for design optimization of microsystems
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    Chapter 1066 A learning classifier system for three-dimensional shape optimization
Overall attention for this book and its chapters
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Mentioned by

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Title
Parallel Problem Solving from Nature — PPSN IV
Published by
Springer Berlin Heidelberg, January 2006
DOI 10.1007/3-540-61723-x
ISBNs
978-3-54-061723-5, 978-3-54-070668-7
Editors

Voigt, Hans-Michael, Ebeling, Werner, Rechenberg, Ingo, Schwefel, Hans-Paul

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 24 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 1 4%
Researcher 1 4%
Lecturer 1 4%
Unknown 21 88%
Readers by discipline Count As %
Environmental Science 1 4%
Energy 1 4%
Engineering 1 4%
Unknown 21 88%