Artificial Evolution
Springer Berlin (Verlag)
978-3-540-33589-4 (ISBN)
Genetic Programming.- Santa Fe Trail Hazards.- Size Control with Maximum Homologous Crossover.- Machine Learning.- A New Classification-Rule Pruning Procedure for an Ant Colony Algorithm.- Swarm-Based Distributed Clustering in Peer-to-Peer Systems.- Simultaneous Optimization of Weights and Structure of an RBF Neural Network.- An Exponential Representation in the API Algorithm for Hidden Markov Models Training.- Applications.- Memetic Algorithms for the MinLA Problem.- Niching in Evolution Strategies and Its Application to Laser Pulse Shaping.- A Modified Genetic Algorithm for the Beam Angle Optimization Problem in Intensity-Modulated Radiotherapy Planning.- Combinatorial Optimization.- On a Property Analysis of Representations for Spanning Tree Problems.- A Cooperative Multilevel Tabu Search Algorithm for the Covering Design Problem.- Enhancements of NSGA II and Its Application to the Vehicle Routing Problem with Route Balancing.- The Importance of Scalability When Comparing Dynamic Weighted Aggregation and Pareto Front Techniques.- Co-evolution.- A Backbone-Based Co-evolutionary Heuristic for Partial MAX-SAT.- Analysing Co-evolution Among Artificial 3D Creatures.- Self-assembling.- A Critical View of the Evolutionary Design of Self-assembling Systems.- Algorithmic Self-assembly by Accretion and by Carving in MGS.- Evolutionary Design of a DDPD Model of Ligation.- Artificial Life and Bioinformatics.- Population Structure and Artificial Evolution.- Outlines of Artificial Life: A Brief History of Evolutionary Individual Based Models.- An Enhanced Genetic Algorithm for Protein Structure Prediction Using the 2D Hydrophobic-Polar Model.- Incorporating Knowledge of Secondary Structures in a L-System-Based Encoding for Protein Folding.- Advances.- The Electromagnetism Meta-heuristic Applied to the Resource-Constrained Project Scheduling Problem.- Applications of Racing Algorithms: An Industrial Perspective.- An Immunological Algorithm for Global Numerical Optimization.- Algorithms (X, sigma, eta): Quasi-random Mutations for Evolution Strategies.
Erscheint lt. Verlag | 18.4.2006 |
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Reihe/Serie | Lecture Notes in Computer Science | Theoretical Computer Science and General Issues |
Zusatzinfo | XI, 310 p. |
Verlagsort | Berlin |
Sprache | englisch |
Maße | 155 x 235 mm |
Gewicht | 1020 g |
Themenwelt | Informatik ► Software Entwicklung ► User Interfaces (HCI) |
Informatik ► Theorie / Studium ► Algorithmen | |
Naturwissenschaften ► Biologie ► Evolution | |
Schlagworte | Adaptation • Algorithm analysis and problem complexity • Artificial Evolution • Artificial Life • Bioinformatics • bio-inspired computing • Cellular Automata • Coevolution • combinatorial optimization • Evolution • evolutionary algorithms • evolutionary computation • evolutionary optimization • Evolutionary Search • Genetic algorithms • genetic programming • learning • machine learning • Natural Computing • Optimization • programming • self-assembling systems |
ISBN-10 | 3-540-33589-7 / 3540335897 |
ISBN-13 | 978-3-540-33589-4 / 9783540335894 |
Zustand | Neuware |
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