表观遗传进化算法建模：一种基于表观遗传调控过程的方法
Modeling epigenetic evolutionary algorithms: An approach based on the epigenetic regulation process
摘要：
许多生物过程一直是探试法的灵感来源，这些方法产生高质量的解决方案来解决优化和搜索问题。本文提出了一种用于进化算法的表观遗传技术，其灵感来自表观遗传调节过程，一种更好地理解个体适应和学习环境的能力的机制。表观遗传调控包括小分子（也称为表观遗传标签）附着于特定基因或从特定基因移除从而影响表型的生物学机制。五个基本要素构成了设计技术的基础：第一，表观遗传标签作为二进制字符串的隐喻表示;第二，用于绑定标签的染色体顶部结构层第三，添加、移除和修改标签的标记功能;第四，表观遗传生长功能，其作用类似于位于等位基因上的标签的解释器或解码器，在评价个体时能够反映表型变异;第五，标签遗传机制。一组实验进行确定所提出的方法的适用性。
英文摘要：
Many biological processes have been the source of inspiration for heuristic methods that generate high-quality solutions to solve optimization and search problems. This thesis presents an epigenetic technique for Evolutionary Algorithms, inspired by the epigenetic regulation process, a mechanism to better understand the ability of individuals to adapt and learn from the environment. Epigenetic regulation comprises biological mechanisms by which small molecules, also known as epigenetic tags, are attached to or removed from a particular gene, affecting the phenotype. Five fundamental elements form the basis of the designed technique: first, a metaphorical representation of Epigenetic Tags as binary strings; second, a layer on chromosome top structure used to bind the tags (the Epigenotype layer); third, a Marking Function to add, remove, and modify tags; fourth, an Epigenetic Growing Function that acts like an interpreter, or decoder of the tags located over the alleles, in such a way that the phenotypic variations can be reflected when evaluating the individuals; and fifth, a tags inheritance mechanism. A set of experiments are performed for determining the applicability of the proposed approach.
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