Information content and maximum entropy of compartmental systems in equilibrium

Autor:	Metzler, Holger, Sierra, Carlos A.
Rok vydání:	2023
Předmět:	Computer Science - Information Theory Condensed Matter - Statistical Mechanics Mathematics - Dynamical Systems
Druh dokumentu:	Working Paper
Popis:	Although compartmental dynamical systems are used in many different areas of science, model selection based on the maximum entropy principle (MaxEnt) is challenging because of the lack of methods for quantifying the entropy for this type of systems. Here, we take advantage of the interpretation of compartmental systems as continuous-time Markov chains to obtain entropy measures that quantify model information content. In particular, we quantify the uncertainty of a single particle's path as it travels through the system as described by path entropy and entropy rates. Path entropy measures the uncertainty of the entire path of a traveling particle from its entry into the system until its exit, whereas entropy rates measure the average uncertainty of the instantaneous future of a particle while it is in the system. We derive explicit formulas for these two types of entropy for compartmental systems in equilibrium based on Shannon information entropy and show how they can be used to solve equifinality problems in the process of model selection by means of MaxEnt. Comment: Code repository: https://github.com/goujou/entropy_and_complexity_in_eq
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2308.10956 Zobrazit plný text záznamu View this record from Arxiv