This volume encloses research articles that were presented at the EVOLVE 2014 International Conference in Beijing, China, July 14, 2014. The book gathers contributions that emerged from the conference tracks, ranging from probability to set oriented numerics and evolutionary computation; all complemented by the bridging purpose of the conference, e.g. Complex Networks and Landscape Analysis, or by the more application oriented perspective. The novelty of the volume, when considering the EVOLVE series, comes from targeting also the practitioner's view. This is supported by the Machine Learning Applied to Networks and Practical Aspects of Evolutionary Algorithms tracks, providing surveys on new application areas, as in the networking area and useful insights in the development of evolutionary techniques, from a practitioner's perspective. Complementary to these directions, the conference tracks supporting the volume, follow on the individual advancements of the subareas constituting the scope of the conference, through the Computational Game Theory, Local Search and Optimization, Genetic Programming, Evolutionary Multi-objective optimization tracks.

Latest research on Probability, Set Oriented Numerics and volutionary Computation Results of EVOLVE 2014 conference held July 1-4 2014 at Beijing, China Written by experts in the field of Evolutionary Computation and Intelligent Computing

Autorentext
Wei Zhang received his Ph.D. degree from The University of Texas Graduate School of Biomedical Sciences. He joined the faculty of M. D. Anderson Cancer Center in 1994 where he is currently an Associate Professor and the Director of the Cancer Genomics Core Laboratory. Dr. Zhang's research programs include cancer genomics and informatics, tumor suppressor genes, and signal transduction studies. Dr. Zhang is an Associate Editor for American Association of Cancer Research journal Clinical Cancer Research, and serves on editorial board of journals Cancer Biology and Therapy, Histology and Histopathology, International Journal of Oncology, BMC Genomics, Technology in Cancer Research and Treatment, and Molecular Cancer.

Inhalt

Set Oriented Numerics.- Computational Game Theory.- Machine Learning Applied to Networks.- Complex Networks and Landscape Analysis.- Local Search and Optimization.- Genetic Programming.- Evolutionary Multiobjective Optimization.- Practical Aspects of Evolutionary Algorithms.