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Produktbild: Parallel Problem Solving from Nature - PPSN IV
Band 1141

Parallel Problem Solving from Nature - PPSN IV International Conference on Evolutionary Computation. The 4th International Conference on Parallel Problem Solving from Nature Berlin, Germany, September 22 - 26, 1996. Proceedings

Aus der Reihe Lecture Notes in Computer Science

97,99 €

inkl. gesetzl. MwSt., Versandkostenfrei

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

04.09.1996

Abbildungen

XVIII, 1058 p.

Herausgeber

Werner Ebeling + weitere

Verlag

Springer Berlin

Seitenzahl

1058

Maße (B/H)

15,5/23,5 cm

Sprache

Englisch

ISBN

978-3-540-61723-5

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

04.09.1996

Abbildungen

XVIII, 1058 p.

Herausgeber

Verlag

Springer Berlin

Seitenzahl

1058

Maße (B/H)

15,5/23,5 cm

Sprache

Englisch

ISBN

978-3-540-61723-5

Herstelleradresse

Springer Nature Customer Service Center GmbH
Europaplatz 3
69115 Heidelberg
DE
ProductSafety@springernature.com

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  • Produktbild: Parallel Problem Solving from Nature - PPSN IV
  • Computational brittleness and the evolution of computer viruses.- Evolutionary computing in multi-agent environments: Speciation and symbiogenesis.- Evolution strategies with subjective selection.- Emergent cooperation for multiple agents using genetic programming.- Evolution programs evolved.- Encoding scheme issues for open-ended artificial evolution.- Hardware evolution at function level.- Coevolutionary life-time learning.- Genetic programs and co-evolution.- Self-assemblage of gene nets in evolution via recruiting of new netters.- A survey of intron research in genetics.- Analytical and numerical investigations of evolutionary algorithms in continuous spaces.- On the asymptotic behavior of multirecombinant Evolution Strategies.- Are long path problems hard for genetic algorithms?.- Random tree generation for genetic programming.- Implicit formae in genetic algorithms.- A probabilistic database approach to the analysis of genetic algorithms.- Mean field analysis of tournament selection on a random manifold.- From recombination of genes to the estimation of distributions I. Binary parameters.- From recombination of genes to the estimation of distributions II. Continuous parameters.- Searching in the presence of noise.- The density of states — A measure of the difficulty of optimisation problems.- On interactive evolutionary algorithms and stochastic mealy automata.- The influence of different coding schemes on the computational complexity of genetic algorithms in function optimization.- An analysis of the effects of neighborhood size and shape on local selection algorithms.- Evolutionary computation at the edge of feasibility.- Dimensional analysis of allele-wise mixing revisited.- Gaussian diffusion in a simple genetic algorithm.- Erroneous truncation selection— A breeder's decision making perspective.- New crossover methods for sequencing problems.- The effect of extensive use of the mutation operator on generalization in genetic programming using sparse data sets.- On permutation representations for scheduling problems.- Multi-parent's niche: N-ary crossovers on NK-landscapes.- A preliminary investigation into directed mutations in evolutionary algorithms.- Heuristic crossovers for real-coded genetic algorithms based on fuzzy connectives.- Are evolutionary algorithms improved by large mutations?.- Mutation by imitation in boolean evolution strategies.- Formal algorithms + formal representations =search strategies.- A genetic algorithm with variable range of local search for tracking changing environments.- An Evolution Strategy with adaptation of the step sizes by a variance function.- Every niching method has its niche: Fitness sharing and implicit sharing compared.- Effects of isolation in a distributed population genetic algorithm.- Self-adaptive genetic algorithm for numeric functions.- Niche search: An evolutionary algorithm for global optimisation.- Adaptively parameterised evolutionary systems: Self adaptive recombination and mutation in a genetic algorithm.- Obtaining multiple distinct solutions with genetic algorithm niching methods.- Cost Based Operator Rate Adaptation: An investigation.- Genetic algorithms and relational landscapes.- IOGA: An instance-oriented genetic algorithm.- Explicit filtering of building blocks for genetic algorithms.- Multi-objective optimization by means of the thermodynamical genetic algorithm.- Adaptation to a changing environment by means of the thermodynamical genetic algorithm.- The development of a dual-agent strategy for efficient search across whole system engineering designhierarchies.- A parallel cellular genetic algorithm used in finite element simulation.- A robust solution searching scheme in genetic search.- Solving MasterMind using GAs and simulated annealing: A case of dynamic constraint optimization.- Evolving compact solutions in genetic programming: A case study.- Climbing up NP-hard hills.- On the performance assessment and comparison of stochastic multiobjective optimizers.- Paginating the generalized newspapers — A comparison of simulated annealing and a heuristic method.- A comparison of optimization techniques for integrated manufacturing planning and scheduling.- A comparison of search techniques on a wing-box optimisation problem.- A comparative study of evolutionary algorithms for on-line parameter tracking.- Modeling urban growth by cellular automata.- Democratic optimization for discrete and continuous systems.- A study of some properties of Ant-Q.- Immunoid: An immunological approach to decentralized behavior arbitration of autonomous mobile robots.- Parallelizable evolutionary dynamics principles for solving the maximum clique problem.- Significance of locality and selection pressure in the grand deluge evolutionary algorithm.- Parallel computing with DNA: Toward the anti-universal machine.- Tackling the “curse of dimensionality” of radial basis functional neural networks using a genetic algorithm.- A Three-stage method for designing Genetic Fuzzy Systems by learning from examples.- Learning heuristics for OBDD minimization by Evolutionary Algorithms.- Improving the generalization performance of multi-layer-perceptrons with population-based incremental learning.- Robust GP in robot learning.- A pattern recognition system using evolvable hardware.- Topology design of feedforward neural networks by geneticalgorithms.- An evolution strategy for on-line optimisation of dynamic objective functions.- Exploiting competing subpopulations for automatic generation of test sequences for digital circuits.- Constraint handling in evolutionary search: A case study of the frequency assignment.- An application of genetic algorithms and neural networks to scheduling power generating systems.- Evolutionary algorithms for the calculation of electron distributions in Si-MOSFETs.- Refueling of a nuclear power plant: Comparison of a naive and a specialized mutation operator.- Genetic algorithms applied to the physical design of VLSI circuits: A survey.- Stochastic methods for transistor size optimization of CMOS VLSI circuits.- An adaptive parallel Genetic Algorithm for VLSI-layout optimization.- Genetic algorithms for protocol validation.- Constraint handling for the fault coverage code generation problem: An inductive evolutionary approach.- New genetic local search operators for the traveling salesman problem.- An evolutionary approach to hardware/software partitioning.- Evolutionary Air Traffic Flow Management for large 3D-problems.- Genetic-based dynamic load balancing: Implementation and evaluation.- Production scheduling with genetic algorithms and simulation.- Network optimization using evolutionary strategies.- Co-evolving parallel random number generators.- Scheduling by genetic local search with multi-step crossover.- Finding the conformation of organic molecules with genetic algorithms.- Investigating a Parallel Breeder Genetic Algorithm on the inverse Aerodynamic design.- An evolutionary design for f-? lenses.- Optimization of heat exchanger networks by means of evolution strategies.- Industrial plant pipe-route optimisation with genetic algorithms.- An evolutionary algorithmfor design optimization of microsystems.- A learning classifier system for three-dimensional shape optimization.