Activatability for simulation tractability of NP problems: Application to Ecology

TL;DR

This paper introduces an activatability-based method to improve the efficiency of ecological system simulations by reducing redundant processes, enabling faster predictions of system trajectories.

Contribution

It proposes a novel search cycle that leverages statistical modeling to minimize processes needed for accurate ecological simulations, enhancing tractability.

Findings

Reduces simulation execution time by eliminating redundant processes.

Converges to minimal process sets matching simulation objectives.

Applicable to large spatial ecological models.

Abstract

Dynamics of biological-ecological systems is strongly depending on spatial dimensions. Most of powerful simulators in ecology take into account for system spatiality thus embedding stochastic processes. Due to the difficulty of researching particular trajectories, biologists and computer scientists aim at predicting the most probable trajectories of systems under study. Doing that, they considerably reduce computation times. However, because of the largeness of space, the execution time remains usually polynomial in time. In order to reduce execution times we propose an activatability-based search cycle through the process space. This cycle eliminates the redundant processes on a statistical basis (Generalized Linear Model), and converges to the minimal number of processes required to match simulation objectives.