“代表性”元启发式设计模式

J. Swan, Zoltan A. Kocsis, A. Lisitsa
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引用次数: 1

摘要

1. 当需要在搜索过程中消除冗余时,“代表性”模式是适用的:•通常情况下,一些对优化感兴趣的函数f给出了一个多对一的映射,即它在f的图像上诱导等价类。如果f是一个适应度函数,这可能会导致适应度出现停滞。•可能是消除冗余允许在更小的(“商”)空间中执行搜索,可以使用不适用于原始空间的方法(甚至可能是精确的技术)进行搜索。•在gp树的情况下,语法上不等价但语义上等价的表示(例如x + x, 2 * x)可能导致基因型到表型映射缺乏梯度,这可能使程序空间更难有效搜索。
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The 'representative' metaheuristic design pattern
1. PROBLEM STATEMENT The ‘Representative’ pattern is applicable when it is desirable to eliminate redundancy in the search process: • It is often the case that some function f of interest in optimization gives a many-to-one mapping, i.e. it induces equivalence classes over the image of f . If f is a fitness function, this can lead to plateaus in the fitness landscape. • It may be that the elimination of redundancy allows search to be performed in a smaller (‘quotient’) space that can be searched using methods (possibly even exact techniques) not applicable to the original space. • In the case of GP-trees, syntactically inequivalent but semantically equivalent representations (e.g. x + x, 2 ∗x) can lead to a lack of gradient in genotype-to-phenotype mappings, which may make the space of programs harder to search effectively.
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