Pragmatic Logic-Based Spatio-Temporal Pattern Checking in Particle-Based Models

Abstract

Particle-based simulation is a powerful approach for modeling systems and processes of entities interacting in continuous space. One way to validate a particle-based simulation is to check for the occurrence of spatio-temporal patterns formed by the particles, for example by statistical model checking. Whereas spatio-temporal logics for describing spatio-temporal patterns exist, they are defined on discrete rather than continuous space. We propose an approach to bridge this gap by automatically translating the output of continuous-space particle-based simulations into an input for discrete-space spatio-temporal logics. The translation is parameterized with information about relevant regions and their development in time. We demonstrate the utility of our approach with a case study in which we successfully apply statistical model-checking to a particle-based cell-biological model. A Java implementation of our approach is available under an open-source license.