arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 1710.01889cond-mat.stat-mechnlin.AOphysics.bio-ph
收藏

二阶随机优化Lévy游动的出现

Emergence of Lévy walks from second order stochastic optimization

Łukasz Kuśmierz, Taro Toyoizumi

摘要:

在自然觅食中,许多生物似乎执行两种不同类型的运动搜索:定向搜索(出租车)和随机搜索。当环境提供线索以引导朝向目标的运动时,观察到前者。后者不涉及明显的记忆或信息处理,可以通过随机游走进行数学建模。我们表明,这两种类型的搜索可以产生一个共同的机制,其中Lévy航班或Lévy步行出现从二阶梯度为基础的搜索与噪声观测。不需要明确的切换机制-相反,定向和随机运动之间的连续过渡取决于成本函数的Hessian矩阵。在大范围的情景中,Lévy尾指数为$α=1$,与以前在觅食生物中的观察结果一致。这些结果表明,采用二阶优化方法可以是一个有用的策略,结合有向搜索和随机搜索的有效功能。

英文摘要:

In natural foraging, many organisms seem to perform two different types of motile search: directed search (taxis) and random search. The former is observed when the environment provides cues to guide motion towards a target. The latter involves no apparent memory or information processing and can be mathematically modeled by random walks. We show that both types of search can be generated by a common mechanism in which Lévy flights or Lévy walks emerge from a second-order gradient-based search with noisy observations. No explicit switching mechanism is required -- instead, continuous transitions between the directed and random motions emerge depending on the Hessian matrix of the cost function. For a wide range of scenarios the Lévy tail index is $α=1$, consistent with previous observations in foraging organisms. These results suggest that adopting a second-order optimization method can be a useful strategy to combine efficient features of directed and random search.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

↑