Titlebook: Natural and Artificial Computation in Engineering and Medical Applications; 5th International Wo José Manuel Ferrández Vicente,José Ramón á

Pudendal-Nerve

污點(diǎn)

Miguel A. Mu?oz,Jonatan Martínez,José Pascual Molina,Pascual González,Antonio Fernández-Caballeror scientists translate the principles of inheritance, variation and natural selection into algorithmic concepts known as EC. They mainly perform randomized search in the domain space. Among its most famous variants are GAs, ES, EP and GP growing more and more together. In the past many heuristic ext

拾落穗

Antonio Collazos,David Fernández-López,Antonio S. Montemayor,Juan José Pantrigo,María Luisa Delgadoed meta-heuristics. Their success depends on adequate parameter settings. The question arises: how can evolutionary algorithms learn parameters automatically during the optimization? Evolution strategies gave an answer decades ago: self-adaptation. Their self-adaptive mutation control turned out to

青石板

Pablo Tribaldos,Juan Serrano-Cuerda,María T. López,Antonio Fernández-Caballero,Roberto J. López-Sastr scientists translate the principles of inheritance, variation and natural selection into algorithmic concepts known as EC. They mainly perform randomized search in the domain space. Among its most famous variants are GAs, ES, EP and GP growing more and more together. In the past many heuristic ext

dermatomyositis

Ant Colony Algorithms for the Dynamic Vehicle Routing Problem with Time Windows,ic routing problems but solving the dynamic variants has not been given an equal amount of attention, while these are even more relevant to most companies in logistics and transportation. In this work an Ant Colony Optimization algorithm for solving the Dynamic Vehicle Routing Problem with Time Wind

珊瑚

Irritate

kindred

Improved Polar Scan-Matching Using an Advanced Line Segmentation Algorithm,orithm to the laser range returns. Additionally, a set of alternative methods based on local and global optimization algorithms is introduced. Results from robot simulation tests are provided for different ranges of laser range return noise and odometry sensor error levels. The results show that the

甜瓜

陶瓷

Multiscale Dynamic Learning in Cognitive Robotics,hitectures to deal with the different time scales a robot must cope with. The most important types of dynamics that occur in different time scales are defined and different mechanisms within a particular cognitive architecture, the Multilevel Darwinist Brain, are suggested to model each one of them.