当前位置: X-MOL 学术Symmetry › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
An Entropic Gradient Structure in the Network Dynamics of a Slime Mold
Symmetry ( IF 2.940 ) Pub Date : 2021-07-29 , DOI: 10.3390/sym13081385
Vincenzo Bonifaci

The approach to equilibrium in certain dynamical systems can be usefully described in terms of information-theoretic functionals. Well-studied models of this kind are Markov processes, chemical reaction networks, and replicator dynamics, for all of which it can be proven, under suitable assumptions, that the relative entropy (informational divergence) of the state of the system with respect to an equilibrium is nonincreasing over time. This work reviews another recent result of this type, which emerged in the study of the network optimization dynamics of an acellular slime mold, Physarum polycephalum. In this setting, not only the relative entropy of the state is nonincreasing, but its evolution over time is crucial to the stability of the entire system, and the equilibrium towards which the dynamics is attracted proves to be a global minimizer of the cost of the network.

中文翻译:

黏菌网络动力学中的熵梯度结构

某些动态系统中的平衡方法可以用信息论泛函有用地描述。这种经过充分研究的模型是马尔可夫过程、化学反应网络和复制动力学,对于所有这些模型,在适当的假设下,可以证明系统状态的相对熵(信息散度)相对于一个均衡是不随时间增加的。这项工作回顾了这种类型的另一个最近的结果,该结果出现在对脱细胞粘菌的网络优化动力学的研究中,Physarum polycephalum. 在这种情况下,不仅状态的相对熵不增加,而且其随时间的演变对整个系统的稳定性至关重要,并且动态被吸引到的平衡被证明是成本的全局最小化网络。
更新日期:2021-07-29
down
wechat
bug