Actionable forecasting as a determinant of function in noisy biological systems

Autor:	Vilar, Jose M. G., Saiz, Leonor
Rok vydání:	2024
Předmět:	Quantitative Biology - Cell Behavior Condensed Matter - Statistical Mechanics Mathematics - Optimization and Control Nonlinear Sciences - Adaptation and Self-Organizing Systems
Druh dokumentu:	Working Paper
Popis:	Continuous adaptation to variable environments is crucial for the survival of living organisms. Here, we analyze how adaptation, forecasting, and resource mobilization towards a target state, termed actionability, interact to determine biological function. We develop a general theory and show that it is possible for organisms to continuously track their optimal state in a dynamic environment by adapting towards an actionable target that incorporates just current information on the optimal state and its rate of change. If the environmental information is precise and readily actionable, it is possible to implement perfect tracking without anticipatory mechanisms, irrespective of the adaptation rate. In contrast, predictive functions, like those of circadian rhythms, are beneficial if sensing the environment is slow or unreliable, as they allow better adaptation with fewer resources. To explore potential actionable forecasting mechanisms, we develop a general approach that implements the adaptation dynamics with forecasting through a dynamics-informed neural network. Comment: 20 pages, 7 figures
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2404.07895 Zobrazit plný text záznamu View this record from Arxiv