Pierre Collet
Artificial Evolution: 9th International Conference, Evolution Artificielle, Ea 2009, Strasbourg, France, October 26-28, 2009. Revised Selected Papers - Lecture Notes in Computer Science / Theoretical Computer Science and General Issues Pierre Collet

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Artificial Evolution: 9th International Conference, Evolution Artificielle, Ea 2009, Strasbourg, France, October 26-28, 2009. Revised Selected Papers - Lecture Notes in Computer Science / Theoretical Computer Science and General Issues

Pierre Collet

Constitutes the proceedings of the 9th International Conference on Artificial Evolution, held in Strasbourg, France, in October 2009.

Marc Notes: Includes bibliographical references and index.; Also issued online. Table of Contents: Theory.- Extremal Optimization Dynamics in Neutral Landscapes: The Royal Road Case.- Improving the Scalability of EA Techniques: A Case Study in Clustering.- Ant Colony Optimization.- MC-ANT: A Multi-Colony Ant Algorithm.- Applications.- Artificial Evolution for 3D PET Reconstruction.- A Hybrid Genetic Algorithm/Variable Neighborhood Search Approach to Maximizing Residual Bandwidth of Links for Route Planning.- Parallelization of an Evolutionary Algorithm on a Platform with Multi-core Processors.- On the Difficulty of Inferring Gene Regulatory Networks: A Study of the Fitness Landscape Generated by Relative Squared Error.- Combinatorial Optimization.- Memetic Algorithms for Constructing Binary Covering Arrays of Strength Three.- A Priori Knowledge Integration in Evolutionary Optimization.- Robotics.- On-Line, On-Board Evolution of Robot Controllers.- The Transfer of Evolved Artificial Immune System Behaviours between Small and Large Scale Robotic Platforms.- Multi-objective Optimization.- An Analysis of Algorithmic Components for Multiobjective Ant Colony Optimization: A Case Study on the Biobjective TSP.- Alternative Fitness Assignment Methods for Many-Objective Optimization Problems.- Genetic Programming.- Evolving Efficient List Search Algorithms.- Semantic Similarity Based Crossover in GP: The Case for Real-Valued Function Regression.- Genetic-Programming Based Prediction of Data Compression Saving.- Machine Learning.- On the Characteristics of Sequential Decision Problems and Their Impact on Evolutionary Computation and Reinforcement Learning.

Mediji	Grāmatas Paperback Book (Grāmata ar mīksto vāku un līmēto muguru)
Izlaists	2010. gada 6. jūlijs
ISBN13	9783642141553
Izdevēji	Springer-Verlag Berlin and Heidelberg Gm
Lapas	207
Izmēri	155 × 234 × 13 mm · 340 g
Valoda	Franču
Redaktors	Collet, Pierre
Redaktors	Legrand, Pierrick
Redaktors	Lutton, Evelyne
Redaktors	Monmarche, Nicolas
Redaktors	Schoenauer, Marc