Regional Control of Probabilistic Cellular Automata

TL;DR

This paper explores a boundary control method for probabilistic cellular automata, enabling targeted behavior manipulation in specific regions, which is crucial for modeling complex stochastic systems across disciplines.

Contribution

It introduces a novel boundary control approach for probabilistic cellular automata, focusing on localized regulation of their stochastic dynamics.

Findings

Boundary control effectively influences target regions in probabilistic cellular automata.

The method provides a new way to steer stochastic systems without full internal intervention.

Potential applications in modeling and controlling complex systems across various fields.

Abstract

Probabilistic Cellular Automata are extended stochastic systems, widely used for modelling phenomena in many disciplines. The possibility of controlling their behaviour is therefore an important topic. We shall present here an approach to the problem of controlling such systems by acting only on the boundary of a target region.