Titlebook: Genetic Programming; First European Works Wolfgang Banzhaf,Riccardo Poli,Terence C. Fogarty Conference proceedings 1998 Springer-Verlag Ber

Sinuate

书目名称Genetic Programming影响因子(影响力)




书目名称Genetic Programming影响因子(影响力)学科排名




书目名称Genetic Programming网络公开度




书目名称Genetic Programming网络公开度学科排名




书目名称Genetic Programming被引频次




书目名称Genetic Programming被引频次学科排名




书目名称Genetic Programming年度引用




书目名称Genetic Programming年度引用学科排名




书目名称Genetic Programming读者反馈




书目名称Genetic Programming读者反馈学科排名

盖他为秘密

Where does the good stuff go, and why? how contextual semantics influences program structure in simty of genetic program trees during the evolutionary process. We show that contextual semantics influence the composition, location and flows of operative code in a program. In detail we analyze these dynamics and discuss the impact of our findings on micro-level descriptions of genetic programming.

变化无常

凹槽

Concepts of inductive genetic programming,g tasks. We review the components of the method, and propose new approaches to some open issues such as: the sensitivity of the operators to the topology of the genetic program trees, the coordination of the operators, and the investigation of their performance. The genetic operators are examined by

Campaign

Immediate transfer of global improvements to all individuals in a population compared to automatica, an improvement in a part of a program (an ADF or a main body) can only be transferred via crossover. In this article, we consider whether it is a good idea to transfer immediately improvements found by a single individual to the whole population. A system that implements this idea has been propose

GULF

Non-destructive depth-dependent crossover for genetic programming,rmal crossover, i.e., building blocks are broken unexpectedly. In the depth-dependent crossover, the depth selection ratio was varied according to the depth of a node. However, the depth-dependent crossover did not work very effectively as generated programs became larger. To overcome this, we intro

GULF

Grammatical evolution: Evolving programs for an arbitrary language,nition is mapped to a program, expressions and programs of arbitrary complexity may be evolved. Other automatic programming methods are described, before our system, ., is applied to a symbolic regression problem.

结构

唤醒

Speech sound discrimination with genetic programming, data of human speech. We examine whether a genetic programming algorithm can find programs that are able to discriminate certain spoken vowels and consonants. We present evidence that this can indeed be achieved with a surprisingly simple approach that does not need preprocessing. The data we have

漂泊

Efficient evolution of asymmetric recurrent neural networks using a PDGP-inspired two-dimensional rent architectures have been hindered by the fact that available training algorithms are considerably more complex than those for feedforward networks. In this paper, we present a new method to build recurrent neural networks based on evolutionary computation, which combines a linear chromosome with