Titlebook: Artificial Evolution; European Conference, Jean-Marc Alliot,Evelyne Lutton,Dominique Snyers Conference proceedings 1996 Springer-Verlag Ber

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暂停,间歇

Immune system and fault-tolerant computing,onsist in detecting erroneous states of an algorithm and executing recovery procedures. They are generally implemented by adding formal properties to be satisfied by state variables during execution. However, defining fault-tolerant procedures can be error-prone and sometimes equivalent to a formal

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fiscal

How long does it take to evolve a neural net?,rom perception to control; in the context of control, achieving great precision is more critical than in pattern recognition or classification tasks. In previous work, the authors have found that when employing genetic search to train a net, both precision and training speed can be greatly enhanced

dry-eye

Kinetic

Interactive evolution for simulated natural evolution,trates how . can be used to study the evolution of simulated natural evolution. Since interactive evolution allows the user to direct the development of models of natural systems, it can be used to direct the evolution of models of animals and plants. We show that interactivity of artificial evoluti

集中营

Building new tools for synthetic image animation by using evolutionary techniques,ow Evolutionary Algorithms can be used as tools to build realistic physical models for image animation..First, a method to detect regions with rigid 2D motion in image sequences, without solving explicitly the Optical Flow equation, is presented. It is based on the resolution of an equation involvin

mettlesome

A genetic algorithm with sharing for the detection of 2D geometric primitives in images,als). This approach completes the well-known Hough Transform, in the sense that GAs are efficient when the Hough approach becomes too expensive in memory, i.e. when we search for complex primitives having more than 3 or 4 parameters..Indeed, a GA is a stochastic technique, relatively slow, but which

飞行员

Conference proceedings 1996veys on evolution strategies and evolutionary programming, 24 full papers are presented. They are grouped into sections on evolutionary computation theory, genetic algorithm techniques, coevolution, neural networks, image processing, and applications to various optimization and other problems.