多头绒泡菌智能觅食行为及其仿生应用研究进展
A Survey on Physarum Polycephalum Intelligent Foraging Behaviour and Bio-Inspired Applications
摘要：
近年来，在Nakagaki等人（2000）进行了著名的实验后，多头绒泡菌的研究变得更加流行，该实验表明绒泡菌能够找到通过迷宫的最短路线。随后的研究证实了物理启发算法解决各种NP难题的能力。与以前的评论，无论是集中在生物方面或生物启发的应用程序，在这里，我们提出了一个全面的审查，突出最近的多头绒泡菌生物方面，数学模型，和绒泡菌生物启发的算法及其应用。这篇综述的新颖性源于我们对绒泡菌属在竞争环境中的智能行为的探索。此外，我们提出了我们的新模型来模拟绒泡菌在竞争中，多个绒泡菌相互作用，并与他们的环境。基于生物启发的绒泡菌在竞争算法中具有很大的研究潜力。
英文摘要：
In recent years, research on Physarum polycephalum has become more popular after Nakagaki et al. (2000) performed their famous experiment showing that Physarum was able to find the shortest route through a maze. Subsequent researches have confirmed the ability of Physarum-inspired algorithms to solve a wide range of NP-hard problems. In contrast to previous reviews that either focus on biological aspects or bio-inspired applications, here we present a comprehensive review that highlights recent Physarum polycephalum biological aspects, mathematical models, and Physarum bio-inspired algorithms and their applications. The novelty of this review stems from our exploration of Physarum intelligent behaviour in competition settings. Further, we have presented our new model to simulate Physarum in competition, where multiple Physarum interact with each other and with their environments. The bio-inspired Physarum in competition algorithms proved to have great potentials for future research.
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。
