A Vivisection of the ev Computer Organism: Identifying Sources of Active Information

George D. Montañez, W. Ewert, W. Dembski, R. Marks
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引用次数: 15

Abstract

ev is an evolutionary search algorithm proposed to simulate biological evolution. As such, researchers have claimed that it demonstrates that a blind, unguided search is able to generate new information. However, analysis shows that any non-trivial computer search needs to exploit one or more sources of knowledge to make the search successful. Search algorithms mine active information from these resources, with some search algorithms performing better than others. We illustrate these principles in the analysis of ev . The sources of knowledge in ev include a Hamming oracle and a perceptron structure that predisposes the search towards its target. The original ev uses these resources in an evolutionary algorithm. Although the evolutionary algorithm finds the target, we demonstrate a simple stochastic hill climbing algorithm uses the resources more efficiently.
计算机有机体的活体解剖:识别活动信息的来源
Ev是一种模拟生物进化的进化搜索算法。因此,研究人员声称,这表明,一个盲目的,无指导的搜索能够产生新的信息。然而,分析表明,任何重要的计算机搜索都需要利用一个或多个知识来源才能使搜索成功。搜索算法从这些资源中挖掘活动信息,其中一些搜索算法比其他搜索算法表现得更好。我们在ev的分析中说明了这些原理。ev中的知识来源包括一个汉明预言和一个感知器结构,该结构使搜索倾向于其目标。原始ev在进化算法中使用这些资源。虽然进化算法可以找到目标,但我们证明了一种简单的随机爬坡算法可以更有效地利用资源。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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