论文标题
生物进化和遗传算法：探索抽象瓷砖自组装的空间
Biological Evolution and Genetic Algorithms: Exploring the Space of Abstract Tile Self-Assembly
论文作者
论文摘要
使用图形处理单元（GPU）实施了基于瓷砖的自组装模型（JATAM）的物理动机遗传算法（GA）和完全枚举。我们观察到有关GA的CPU最新实施的性能提高，JATAM为2.9。使用测试床的健身函数证明了GA实现的正确性，并且通过基于两种瓷砖类型对知名搜索空间$ s_ {2,8} $进行分类来验证我们的JATAM实现。实现的性能获得允许将较大的搜索空间分类$ s^{32} _ {3,8} $基于三种瓷砖类型。基于两种瓷砖类型的结构的普遍性表明，即使在复杂的生态系统中，简单的生物也可以选择出现。发现最大结构的模块化激发了以下假设：$ s_ {2,8} $形成$ s_ {3,8} $的构建块。我们得出的结论是，GPU可能在进化动力学的未来研究中起重要作用。
A physically-motivated genetic algorithm (GA) and full enumeration for a tile-based model of self-assembly (JaTAM) is implemented using a graphics processing unit (GPU). We observe performance gains with respect to state-of-the-art implementations on CPU of factor 7.7 for the GA and 2.9 for JaTAM. The correctness of our GA implementation is demonstrated using a test-bed fitness function, and our JaTAM implementation is verified by classifying a well-known search space $S_{2,8}$ based on two tile types. The performance gains achieved allow for the classification of a larger search space $S^{32}_{3,8}$ based on three tile types. The prevalence of structures based on two tile types demonstrates that simple organisms emerge preferrably even in complex ecosystems. The modularity of the largest structures found motivates the assumption that to first order, $S_{2,8}$ forms the building blocks of $S_{3,8}$. We conclude that GPUs may play an important role in future studies of evolutionary dynamics.
