Yu Tina, Miller Julian Francis
Department of Computer Science, Memorial University of Newfoundland, St. John's, NL A1B 3X5, Canada.
Artif Life. 2006 Fall;12(4):525-51. doi: 10.1162/artl.2006.12.4.525.
An evolutionary system that supports the interaction of neutral and adaptive mutations is investigated. Experimental results on a Boolean function and needle-in-haystack problems show that this system enables evolutionary search to find better solutions faster. Through a novel analysis based on the ratio of neutral to adaptive mutations, we identify this interaction as an engine that automatically adjusts the relative amounts of exploration and exploitation to achieve effective search (i.e., it is self-adaptive). Moreover, a hypothesis to describe the search process in this system is proposed and investigated. Our findings lead us to counter the arguments of those who dismiss the usefulness of neutrality. We argue that the benefits of neutrality are intimately related to its implementation, so that one must be cautious about making general claims about its merits or demerits.
研究了一种支持中性突变和适应性突变相互作用的进化系统。关于布尔函数和大海捞针问题的实验结果表明，该系统能使进化搜索更快地找到更好的解决方案。通过基于中性突变与适应性突变比例的新颖分析，我们将这种相互作用识别为一种自动调整探索和利用相对量以实现有效搜索的引擎（即它是自适应的）。此外，还提出并研究了一个描述该系统搜索过程的假设。我们的研究结果促使我们反驳那些否定中性突变有用性的观点。我们认为，中性突变的益处与其实现方式密切相关，因此在对其优缺点进行一般性断言时必须谨慎。
