Titlebook: Introduction to Evolutionary Computing; A. E. Eiben,J. E. Smith Textbook 20031st edition Springer-Verlag Berlin Heidelberg 2003 Evolution

向下

Genetic Programming, trees as chromosomes), it differs from other EA strands in its application area. While the EAs discussed so far are typically applied to optimisation problems, GP could instead be positioned in machine learning. In terms of the different problem types as discussed in Chapter 1, most other EAs are f

下邊深陷

Flu表流動

Incise

Multimodal Problems and Spatial Distribution,feature affecting the likelihood of an individual taking part in the creation of new offspring, and surviving to the next generation. However we know that evolution in vivo is also affected by another major parameter, namely that of the physical space within which evolution occurs, which imposes a s

陳列

atopic

Theory,Holy Grail” of these efforts is the formulation of predictive models describing the behaviour of an EA on arbitrary problems, and permitting the specification of the most efficient form of optimiser for any given problem. However, (at least in the authors’ opinions) this is unlikely ever to be reali

優(yōu)雅

Constraint Handling,al problems are constrained. It is also a theoretically challenging subject since a great deal of intractable problems (NP-hard, NP-complete, etc.) are constrained. The presence of constraints has the effect that not all possible combinations of variable values represent valid solutions to the probl

使成波狀

Special Forms of Evolution,coevolution and interactive evolution that both work under “external influence”. In coevolution the influence comes from another population, whose members affect the fitness of the main population. In turn, the main population also influences the fitness of the other one; hence the two populations e

vascular

Virtues

Summary,ialects have emerged independently to some extent (except GP that grew out of GAs) and developed their own terminology, research focus, and technical solutions to realise particular evolutionary algorithm features. The differences between them, however, are not crisp — there are many examples of EAs