Incremental Evaluation in Genetic Programming
Incremental Evaluation in Genetic Programming
复制标题
遗传编程中的增量评估
DOI：
--
复制
发表时间：
2021
期刊：
影响因子：
--
通讯作者：
W. Langdon
中科院分区：
文献类型：
--
作者：
W. Langdon
GP通常会以任何顺序评估这些纯粹的功能表达式。距离句法破坏的距离（例如，交叉点）可以在解释整个孩子之前达到零因此，它的效果与其父级相同（妈妈）。平行计算16个核心桌面可以每秒提供5710亿GP操作，571 GIGA GPOP/s。平滑的景观和软件可塑性，这会使源代码的功能弹性平均变化。 。
. Often GP evolves side effect free trees. These pure functional expressions can be evaluated in any order. In particular they can be interpreted from the genetic modification point outwards. Incremental evaluation exploits the fact that: in highly evolved children the semantic difference between child and parent falls with distance from the syntactic disruption (e.g. crossover point) and can reach zero before the whole child has been interpreted. If so, its fitness is identical to its parent (mum). Considerable savings in bloated binary tree GP runs are given by exploiting population convergence with existing GPquick data structures, leading to near linear O(gens) runtime. With multi-threading and SIMD AVX parallel computing a 16 core desktop can deliver the equivalent of 571 billion GP operations per second, 571 giga GPop/s. GP convergence is viewed via information theory as evolving a smooth landscape and software plasticity. Which gives rise to functional resilience to source code changes. On average a mixture of 100 +, -, × and (protected) ÷ tree nodes remove test case effectiveness at exposing changes and so fail to propagate crossover infected errors.
DOI：
10.1109/icse.2015.71
发表时间：
2015-05
期刊：
2015 IEEE/ACM 37th IEEE International Conference on Software Engineering
影响因子：
--
作者：
Yue Jia;Myra B. Cohen;M. Harman;J. Petke
通讯作者：
Yue Jia;Myra B. Cohen;M. Harman;J. Petke
归一化挤压性和失败的错误传播
影响因子：
0.5
作者：
Clark D
通讯作者：
Clark D
影响因子：
14.3
作者：
Petke J
通讯作者：
Petke J