2000, ISBN: 9783540410560
Springer, Taschenbuch, Auflage: 2000, 958 Seiten, Publiziert: 2000-09-06T00:00:01Z, Produktgruppe: Buch, Hersteller-Nr.: 26202992, 1.29 kg, Informatik, IT-Ausbildung & -Berufe, Computer &… Mehr…
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2000, ISBN: 9783540410560
Springer, Taschenbuch, Auflage: 2000, 958 Seiten, Publiziert: 2000-09-06T00:00:01Z, Produktgruppe: Buch, Hersteller-Nr.: 26202992, 1.29 kg, Informatik, IT-Ausbildung & -Berufe, Computer &… Mehr…
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2000, ISBN: 3540410562
[EAN: 9783540410560], Neubuch, [SC: 0.0], [PU: Springer Berlin Heidelberg], ALGORITHMUS KOMPLEXE ZAHLEN ZAHL INTELLIGENZ KÜNSTLICHE KI - AI PROGRAMMIEREN (EDV) PARALLEL BIOLOGIE MENSCH BI… Mehr…
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2000, ISBN: 9783540410560
Taschenbuch
[ED: Kartoniert / Broschiert], [PU: Springer Berlin Heidelberg], We are proud to introduce the proceedings of the Sixth International Conference on Parallel Problem Solving from Nature, P… Mehr…
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2000, ISBN: 9783540410560
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Parallel Problem Solving from Nature-PPSN VI: 6th International Conference, Paris, France, September 18-20 2000 Proceedings (Lecture Notes in Computer Science, 1917, Band 1917) - Taschenbuch
2000, ISBN: 9783540410560
Springer, Taschenbuch, Auflage: 2000, 958 Seiten, Publiziert: 2000-09-06T00:00:01Z, Produktgruppe: Buch, Hersteller-Nr.: 26202992, 1.29 kg, Informatik, IT-Ausbildung & -Berufe, Computer &… Mehr…
2000, ISBN: 9783540410560
Springer, Taschenbuch, Auflage: 2000, 958 Seiten, Publiziert: 2000-09-06T00:00:01Z, Produktgruppe: Buch, Hersteller-Nr.: 26202992, 1.29 kg, Informatik, IT-Ausbildung & -Berufe, Computer &… Mehr…
2000
ISBN: 3540410562
[EAN: 9783540410560], Neubuch, [SC: 0.0], [PU: Springer Berlin Heidelberg], ALGORITHMUS KOMPLEXE ZAHLEN ZAHL INTELLIGENZ KÜNSTLICHE KI - AI PROGRAMMIEREN (EDV) PARALLEL BIOLOGIE MENSCH BI… Mehr…
2000, ISBN: 9783540410560
Taschenbuch
[ED: Kartoniert / Broschiert], [PU: Springer Berlin Heidelberg], We are proud to introduce the proceedings of the Sixth International Conference on Parallel Problem Solving from Nature, P… Mehr…
2000, ISBN: 9783540410560
Springer, 2000-10-13. Paperback. Used: Good., Springer, 2000-10-13, 2.5
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Detailangaben zum Buch - Parallel Problem Solving from Nature-PPSN VI: 6th International Conference, Paris, France, September 18-20 2000 Proceedings (Lecture Notes in Computer Science, 1917, Band 1917)
EAN (ISBN-13): 9783540410560
ISBN (ISBN-10): 3540410562
Gebundene Ausgabe
Taschenbuch
Erscheinungsjahr: 2000
Herausgeber: Schoenauer, Marc, Deb, Kalyanmoy, Rudolph, Günther, Yao, Xin, Lutton, Evelyne, Merelo, Juan Julian, Schwefel, Hans-Paul, Springer
Buch in der Datenbank seit 2007-10-04T20:02:50+02:00 (Berlin)
Detailseite zuletzt geändert am 2024-04-16T18:15:18+02:00 (Berlin)
ISBN/EAN: 9783540410560
ISBN - alternative Schreibweisen:
3-540-41056-2, 978-3-540-41056-0
Alternative Schreibweisen und verwandte Suchbegriffe:
Autor des Buches: günther hans, paul rudolph, kalyanmoy deb, evelyn paul, hans paul schwefel, schönauer, gunther, julia hans, schoen paul, marc, springer, xin, julian hans
Titel des Buches: paris, natur 2000, 2000 solved problems, problem, parallel, september, proceedings from, proceedings conference, international proceedings, our nature, nature international science, france
Daten vom Verlag:
Autor/in: Marc Schoenauer; Kalyanmoy Deb; Günther Rudolph; Xin Yao; Evelyne Lutton; Juan Julian Merelo; Hans-Paul Schwefel
Titel: Lecture Notes in Computer Science; Parallel Problem Solving from Nature-PPSN VI - 6th International Conference, Paris, France, September 18-20 2000 Proceedings
Verlag: Springer; Springer Berlin
916 Seiten
Erscheinungsjahr: 2000-09-06
Berlin; Heidelberg; DE
Gedruckt / Hergestellt in Deutschland.
Gewicht: 1,413 kg
Sprache: Englisch
106,99 € (DE)
109,99 € (AT)
118,00 CHF (CH)
POD
XLII, 916 p.
BC; Programming Techniques; Hardcover, Softcover / Informatik, EDV/Informatik; Computerprogrammierung und Softwareentwicklung; Verstehen; Algorithms; algorithm; combinatorial optimization; evolutionary algorithm; genetic programming; learning; machine learning; optimization; programming; scheduling; theory of evolution; algorithm analysis and problem complexity; Computation by Abstract Devices; Algorithm Analysis and Problem Complexity; Artificial Intelligence; Computer Appl. in Life Sciences; Programming Techniques; Theory of Computation; Algorithms; Artificial Intelligence; Computational and Systems Biology; Theoretische Informatik; Algorithmen und Datenstrukturen; Künstliche Intelligenz; DV-gestützte Biologie/Bioinformatik; EA
Invited Papers.- Interacting Trajectories in Design Space and Niche Space: A Philosopher Speculates About Evolution.- Language as a Complex Adaptive System.- Analysis and Theory of EAs.- Cellular Evolutionary Algorithms: Evaluating the Influence of Ratio.- Efficiency and Mutation Strength Adaptation of the (?/? I, ?)-ES in a Noisy Environment.- An Analysis of the Configuration Space of the Maximal Constraint Satisfaction Problem.- On the Desired Behaviors of Self-Adaptive Evolutionary Algorithms.- Practical Implications of New Results in Conservation of Optimizer Performance.- Large Deviations, Evolutionary Computation and Comparisons of Algorithms.- On the Choice of the Mutation Probability for the (1+1) EA.- The Genetic Code-Like Transformations and Their Effect on Learning Functions.- Perturbation Theory for Evolutionary Algorithms: Towards an Estimation of Convergence Speed.- Statistical Characteristics of Evolution Strategies.- Consensus Sequence Plots and Error Thresholds: Tools for Visualising the Structure of Fitness Landscapes.- Experiments with Tuneable Fitness Landscapes.- Introducing a New Persistence Measure.- An Analysis of Dynamic Severity and Population Size.- Functions as Permutations: Regarding No Free Lunch, Walsh Analysis and Summary Statistics.- Genetic Programming.- Distributed Hybrid Genetic Programming for Learning Boolean Functions.- Genetic Programming with Dynamic Fitness for a Remote Sensing Application.- Genetic Programming Bloat without Semantics.- Genetic Programming and Domain Knowledge: Beyond the Limitations of Grammar-Guided Machine Discovery.- Polymorphy and Hybridization in Genetically Programmed Networks.- Building Optimal Committees of Genetic Programs.- Scheduling.- Distributed Simulated Annealing for Job Shop Scheduling.- Anticipation in Dynamic Optimization: The Scheduling Case.- Multirecombinated Evolutionary Algorithms for the Flow Shop Scheduling Problem.- GA Based on the UV-Structure Hypothesis and Its Application to JSP.- Neighbourhood Based Robustness Applied to Tardiness and Total Flowtime Job Shops.- Solving Extended Hybrid-Flow-Shop Problems Using Active Schedule Generation and Genetic Algorithms.- A Comparison of Genetic Algorithms for the Static Job Shop Scheduling Problem.- Representations and Operators.- An Emperical Study on GAs “Without Parameters”.- Using Dynastic Exploring Recombination to Promote Diversity in Genetic Search.- Adaptive Control of the Mutation Probability by Fuzzy Logic Controllers.- A Comparison of Two Representations for the Fixed Charge Transportation Problem.- Invariance, Self-Adaptation and Correlated Mutations in Evolution Strategies.- Theoretical Analysis of Simplex Crossover for Real-Coded Genetic Algorithms.- Applying Self-Organised Criticality to Evolutionary Algorithms.- Genetic Algorithms, Clustering, and the Breaking of Symmetry.- Pruefer Numbers and Genetic Algorithms: A Lesson on How the Low Locality of an Encoding Can Harm the Performance of Gas.- Median-Selection for Parallel Steady-State Evolution Strategies.- The Origination of Diversity by Adaptive Clustering.- Symbiotic Combination as an Alternative to Sexual Recombination in Genetic Algorithms.- Co-evolution.- Island Model Cooperating with Speciation for Multimodal Optimization.- Optimizing through Co-evolutionary Avalanches.- Evolution of Altruism in Viscous Populations: Effects of Altruism on the Evolution of Migrating Behavior.- A Game-Theoretic Approach to the Simple Coevolutionary Algorithm.- The Number of People with Whom a Man Interacts.- NK-landscapes as Test Functions for Evaluation of Host-Parasite Algorithms.- Towards Balanced Coevolution.- Spatial Games with Adaptive Tit-for-Tats.- Competitive Segmentation: A Struggle for Image Space.- Constraint Handling Techniques.- An Adaptive Algorithm for Constrained Optimization Problems.- Test-Case Generator TCG-2 for Nonlinear Parameter Optimisation.- Solving CSP Instances Beyond the Phase Transition Using Stochastic Search Algorithms.- Noisy and Non-stationary Environments.- Steady-State Evolutionary Path Planning, Adaptive Replacement, and Hyper-Diversity.- Optimization of Noisy Fitness Functions by Means of Genetic Algorithms Using History of Search.- Evolvable Hardware and Hardware Implementation of EAs.- An Efficient Random Number Generation Architecture for Hardware Parallel Genetic Algorithms.- An Integrated On-Line Learning System for Evolving Programmable Logic Array Controllers.- Combinatorial Optimisation.- Selection and Reinforcement Learning for Combinatorial Optimization.- Ant Colony Optimization for the Total Weighted Tardiness Problem.- Adaptive Fitness Functions for the Satisfiability Problem.- Large-Scale Permutation Optimization with the Ordering Messy Genetic Algorithm.- A Hybrid GA for the Edge-Biconnectivity Augmentation Problem.- A Temporal Representation for GA and TSP.- A Comparison of Nature Inspired Heuristics on the Traveling Salesman Problem.- A Genetic Algorithm for VLSI Floorplanning.- Applications.- Scalability and Efficiency of Genetic Algorithms for Geometrical Applications.- Genetic Optimization of the EPR Spectral Parameters: Algorithm Implementation and Preliminary Results.- Fitting Fluorescence Spectra with Genetic Algorithms.- Real-Coded Adaptive Range Genetic Algorithm Applied to Transonic Wing Optimization.- Stream Cyphers with One- and Two-Dimensional Cellular Automata.- Machine Learning and Classifier Systems.- Investigating Generalization in the Anticipatory Classifier System.- A New Bootstrapping Method to Improve Classification Performance in Learning Classifier Systems.- Towards Automatic Domain Knowledge Extraction for Evolutionary Heuristics.- New Algorithms and Metaphors.- Expanding from Discrete to Continuous Estimation of Distribution Algorithms: The ID A.- A New Genetic Algorithms Working on State Domain Order Statistics.- A Factorized Distribution Algorithm Using Single Connected Bayesian Networks.- Optimization as Side-Effect of Evolving Allelopathic Diversity.- Reaction-Diffusion Model of a Honeybee Colony’s Foraging Behaviour.- A Religion-Based Spatial Model for Evolutionary Algorithms.- Bayesian Evolutionary Optimization Using Helmholtz Machines.- Multiobjective Optimisation.- The Pareto Envelope-Based Selection Algorithm for Multiobjective Optimization.- A Fast Elitist Non-dominated Sorting Genetic Algorithm for Multi-objective Optimization: NSGA-II.- Mechanical Component Design for Multiple Ojectives Using Elitist Non-dominated Sorting GA.- On the Assessment of Multiobjective Approaches to the Adaptive Distributed Database Management Problem.- A Hierarchical Genetic Algorithm Using Multiple Models for Optimization.- EA Software.- Take It EASEA.- Evolutionary Computation Visualization: Application to G-PROP.Weitere, andere Bücher, die diesem Buch sehr ähnlich sein könnten:
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