Sumpter D J, Blanchard G B, Broomhead D S
Centre for Mathematical Biology, Mathematical Institute, 24-29 St Giles', Oxford OX1 3LB, U.K.
Bull Math Biol. 2001 Sep;63(5):951-80. doi: 10.1006/bulm.2001.0252.
Process algebras are widely used in the analysis of distributed computer systems. They allow formal reasoning about how the various components of a system contribute to its overall behaviour. In this paper we show how process algebras can be usefully applied to understanding social insect biology, in particular to studying the relationship between algorithmic behaviour of individual insects and the dynamical behaviour of their colony. We argue that process algebras provide a useful formalism for understanding this relationship, since they combine computer simulation, Markov chain analysis and mean-field methods of analysis. Indeed, process algebras can provide a framework for relating these three methods of analysis to each other and to experiments. We illustrate our approach with a series of graded examples of modelling activity in ant colonies.
进程代数在分布式计算机系统分析中被广泛应用。它们允许对系统的各个组件如何对其整体行为做出贡献进行形式化推理。在本文中,我们展示了进程代数如何能够有效地应用于理解群居昆虫生物学,特别是用于研究个体昆虫的算法行为与其群体动态行为之间的关系。我们认为进程代数为理解这种关系提供了一种有用的形式体系,因为它们结合了计算机模拟、马尔可夫链分析和平均场分析方法。实际上,进程代数可以提供一个框架,将这三种分析方法相互关联起来,并与实验相关联。我们用一系列关于蚁群活动建模的分级示例来说明我们的方法。