1 University of New Mexico , Albuquerque, NM , USA.
2 Instituto Tecnológico Autónomo de México, Mexico DF , Mexico.
Philos Trans R Soc Lond B Biol Sci. 2019 Jun 10;374(1774):20180375. doi: 10.1098/rstb.2018.0375.
Brains are composed of connected neurons that compute by transmitting signals. The neurons are generally fixed in space, but the communication patterns that enable information processing change rapidly. By contrast, other biological systems, such as ant colonies, bacterial colonies, slime moulds and immune systems, process information using agents that communicate locally while moving through physical space. We refer to systems in which agents are strongly connected and immobile as solid, and to systems in which agents are not hardwired to each other and can move freely as liquid. We ask how collective computation depends on agent movement. A liquid cellular automaton (LCA) demonstrates the effect of movement and communication locality on consensus problems. A simple mathematical model predicts how these properties of the LCA affect how quickly information propagates through the system. While solid brains allow complex network structures to move information over long distances, mobility provides an alternative way for agents to transport information when long-range connectivity is expensive or infeasible. Our results show how simple mobile agents solve global information processing tasks more effectively than similar systems that are stationary. This article is part of the theme issue 'Liquid brains, solid brains: How distributed cognitive architectures process information'.
大脑由通过传递信号进行计算的连接神经元组成。神经元通常固定在空间中，但能够快速改变的信息处理的通信模式。相比之下，其他生物系统，如蚁群、细菌群落、黏菌和免疫系统，使用在物理空间中移动时进行局部通信的代理来处理信息。我们将强连接且固定不动的系统称为固体，将彼此之间没有硬连线且可以自由移动的系统称为液体。我们询问集体计算如何依赖于代理的移动。一个液体细胞自动机（LCA）演示了运动和通信局部性对共识问题的影响。一个简单的数学模型预测了 LCA 的这些特性如何影响信息在系统中传播的速度。虽然固体大脑允许复杂的网络结构在长距离上移动信息，但当远程连接昂贵或不可行时，移动性为代理提供了一种传输信息的替代方法。我们的结果表明，简单的移动代理如何比类似的静止系统更有效地解决全局信息处理任务。本文是主题为“液体大脑，固体大脑：分布式认知架构如何处理信息”的一部分。
