Eiben5th International Conference, Amsterdam, The Netherlands, September 27-30, 1998, Proceedings
Parallel Problem Solving from Nature - PPSN V
5th International Conference, Amsterdam, The Netherlands, September 27-30, 1998, Proceedings
Herausgegeben:Eiben, Agoston E.; Bäck, Thomas; Schoenauer, Marc; Schwefel, Hans-Paul
Eiben5th International Conference, Amsterdam, The Netherlands, September 27-30, 1998, Proceedings
Parallel Problem Solving from Nature - PPSN V
5th International Conference, Amsterdam, The Netherlands, September 27-30, 1998, Proceedings
Herausgegeben:Eiben, Agoston E.; Bäck, Thomas; Schoenauer, Marc; Schwefel, Hans-Paul
- Broschiertes Buch
- Merkliste
- Auf die Merkliste
- Bewerten Bewerten
- Teilen
- Produkt teilen
- Produkterinnerung
- Produkterinnerung
This book constitutes the refereed proceedings of the 5th International Conference on Parallel Problem Solving from Nature, PPSN V, held in Amsterdam, The Netherlands, in September 1998. The 101 papers included in their revised form were carefully reviewed and selected from a total of 185 submissions. The book is divided into topical sections on convergence theory; fitness landscape and problem difficulty; noisy and non-stationary objective functions; multi-criteria and constrained optimization; representative issues; selection, operators, and evolution schemes; coevolution and learning;…mehr
This book constitutes the refereed proceedings of the 5th International Conference on Parallel Problem Solving from Nature, PPSN V, held in Amsterdam, The Netherlands, in September 1998.
The 101 papers included in their revised form were carefully reviewed and selected from a total of 185 submissions. The book is divided into topical sections on convergence theory; fitness landscape and problem difficulty; noisy and non-stationary objective functions; multi-criteria and constrained optimization; representative issues; selection, operators, and evolution schemes; coevolution and learning; cellular automata, fuzzy systems, and neural networks; ant colonies, immune systems, and other paradigms; TSP, graphs, and satisfiability; scheduling, partitioning, and packing; design and telecommunications; and model estimations and layout problems.
The 101 papers included in their revised form were carefully reviewed and selected from a total of 185 submissions. The book is divided into topical sections on convergence theory; fitness landscape and problem difficulty; noisy and non-stationary objective functions; multi-criteria and constrained optimization; representative issues; selection, operators, and evolution schemes; coevolution and learning; cellular automata, fuzzy systems, and neural networks; ant colonies, immune systems, and other paradigms; TSP, graphs, and satisfiability; scheduling, partitioning, and packing; design and telecommunications; and model estimations and layout problems.
Produktdetails
- Produktdetails
- Lecture Notes in Computer Science 1498
- Verlag: Springer / Springer Berlin Heidelberg / Springer, Berlin
- Artikelnr. des Verlages: 978-3-540-65078-2
- 1998.
- Seitenzahl: 1585
- Englisch
- Abmessung: 56mm x 155mm x 237mm
- Gewicht: 1323g
- ISBN-13: 9783540650782
- ISBN-10: 3540650784
- Artikelnr.: 09224495
- Herstellerkennzeichnung Die Herstellerinformationen sind derzeit nicht verfügbar.
- Lecture Notes in Computer Science 1498
- Verlag: Springer / Springer Berlin Heidelberg / Springer, Berlin
- Artikelnr. des Verlages: 978-3-540-65078-2
- 1998.
- Seitenzahl: 1585
- Englisch
- Abmessung: 56mm x 155mm x 237mm
- Gewicht: 1323g
- ISBN-13: 9783540650782
- ISBN-10: 3540650784
- Artikelnr.: 09224495
- Herstellerkennzeichnung Die Herstellerinformationen sind derzeit nicht verfügbar.
Modelling genetic algorithms: From Markov chains to dependence with complete connections.- On the optimization of unimodal functions with the (1+1) evolutionary algorithm.- A timing analysis of convergence to fitness sharing equilibrium.- Where elitists start limping evolution strategies at ridge functions.- A bit-wise epistasis measure for binary search spaces.- Inside GA dynamics: Ground basis for comparison.- The effect of spin-flip symmetry on the performance of the simple GA.- Fitness distance correlation and Ridge functions.- Accelerating the convergence of evolutionary algorithms by fitness landscape approximation.- Modeling building-block interdependency.- Mutate large, but inherit small! On the analysis of rescaled mutations in ( )-ES with noisy fitness data.- Creating robust solutions by means of evolutionary algorithms.- Analytic curve detection from a noisy binary edge map using genetic algorithm.- A comparison of dominance mechanisms and simple mutation on non-stationary problems.- Adaptation to a changing environment by means of the feedback thermodynamical genetic algorithm.- Optimization with noisy function evaluations.- On risky methods for local selection under noise.- Polygenic inheritance - A haploid scheme that can outperform diploidy.- Averaging efficiently in the presence of noise.- Solving binary constraint satisfaction problems using evolutionary algorithms with an adaptive fitness function.- Varying fitness functions in genetic algorithms: Studying the rate of increase of the dynamic penalty terms.- Landscape changes and the performance of Mapping Based Constraint handling methods.- A decoder-based evolutionary algorithm for constrained parameter optimization problems.- A spatial predator-prey approach to multi-objective optimization: A preliminary study.- Selective breeding in a multiobjective genetic algorithm.- Niching and elitist models for MOGAs.- Parallel evolutionary optimisation with constraint propagation.- Methods to evolve legal phenotypes.- Multiobjective optimization using evolutionary algorithms - A comparative case study.- Utilizing dynastically optimal forma recombination in hybrid genetic algorithms.- Further experimentations on the scalability of the GEMGA.- Indexed memory as a generic protocol for handling vectors of data in genetic programming.- On genetic algorithms and lindenmayer systems.- Genome length as an evolutionary self-adaptation.- Restart scheduling for genetic algorithms.- A comparative study of global and local selection in evolution strategies.- UEGO, an abstract niching technique for global optimization.- Development of problem-specific evolutionary algorithms.- The effects of control parameters and restarts on search stagnation in evolutionary programming.- Accelerating the evolutionary-gradient-search procedure: Individual step sizes.- Extending population-based incremental learning to continuous search spaces.- Multi-parent recombination in genetic algorithms with search space boundary extension by mirroring.- Selective crossover in genetic algorithms: An empirical study.- Line-breeding schemes for combinatorial optimization.- Finding regions of uncertainty in learned models: An application to face detection.- On ZCS in multi-agent environments.- Empirical analysis of the factors that affect the Baldwin effect.- Promoting generalisation of learned behaviours in genetic programming.- Generalization in Wilson's classifier system.- Symbiotic coevolution of artificial neural networks and training data sets.- Information-theoretic analysis of a mobile agent's learning in a discrete state space.- The coevolution of antibodies for concept learning.- Does data-model co-evolution improve generalization performance of evolving learners?.- A corporate classifier system.- Applying diffusion to a cooperative coevolutionary model.- Studying parallel evolutionary algorithms: The cellular programming case.- Learning to avoid moving obstacles optimally for mobile robots using a
Modelling genetic algorithms: From Markov chains to dependence with complete connections.- On the optimization of unimodal functions with the (1+1) evolutionary algorithm.- A timing analysis of convergence to fitness sharing equilibrium.- Where elitists start limping evolution strategies at ridge functions.- A bit-wise epistasis measure for binary search spaces.- Inside GA dynamics: Ground basis for comparison.- The effect of spin-flip symmetry on the performance of the simple GA.- Fitness distance correlation and Ridge functions.- Accelerating the convergence of evolutionary algorithms by fitness landscape approximation.- Modeling building-block interdependency.- Mutate large, but inherit small! On the analysis of rescaled mutations in ( )-ES with noisy fitness data.- Creating robust solutions by means of evolutionary algorithms.- Analytic curve detection from a noisy binary edge map using genetic algorithm.- A comparison of dominance mechanisms and simple mutation on non-stationary problems.- Adaptation to a changing environment by means of the feedback thermodynamical genetic algorithm.- Optimization with noisy function evaluations.- On risky methods for local selection under noise.- Polygenic inheritance - A haploid scheme that can outperform diploidy.- Averaging efficiently in the presence of noise.- Solving binary constraint satisfaction problems using evolutionary algorithms with an adaptive fitness function.- Varying fitness functions in genetic algorithms: Studying the rate of increase of the dynamic penalty terms.- Landscape changes and the performance of Mapping Based Constraint handling methods.- A decoder-based evolutionary algorithm for constrained parameter optimization problems.- A spatial predator-prey approach to multi-objective optimization: A preliminary study.- Selective breeding in a multiobjective genetic algorithm.- Niching and elitist models for MOGAs.- Parallel evolutionary optimisation with constraint propagation.- Methods to evolve legal phenotypes.- Multiobjective optimization using evolutionary algorithms - A comparative case study.- Utilizing dynastically optimal forma recombination in hybrid genetic algorithms.- Further experimentations on the scalability of the GEMGA.- Indexed memory as a generic protocol for handling vectors of data in genetic programming.- On genetic algorithms and lindenmayer systems.- Genome length as an evolutionary self-adaptation.- Restart scheduling for genetic algorithms.- A comparative study of global and local selection in evolution strategies.- UEGO, an abstract niching technique for global optimization.- Development of problem-specific evolutionary algorithms.- The effects of control parameters and restarts on search stagnation in evolutionary programming.- Accelerating the evolutionary-gradient-search procedure: Individual step sizes.- Extending population-based incremental learning to continuous search spaces.- Multi-parent recombination in genetic algorithms with search space boundary extension by mirroring.- Selective crossover in genetic algorithms: An empirical study.- Line-breeding schemes for combinatorial optimization.- Finding regions of uncertainty in learned models: An application to face detection.- On ZCS in multi-agent environments.- Empirical analysis of the factors that affect the Baldwin effect.- Promoting generalisation of learned behaviours in genetic programming.- Generalization in Wilson's classifier system.- Symbiotic coevolution of artificial neural networks and training data sets.- Information-theoretic analysis of a mobile agent's learning in a discrete state space.- The coevolution of antibodies for concept learning.- Does data-model co-evolution improve generalization performance of evolving learners?.- A corporate classifier system.- Applying diffusion to a cooperative coevolutionary model.- Studying parallel evolutionary algorithms: The cellular programming case.- Learning to avoid moving obstacles optimally for mobile robots using a