Intrinsic Simulations and Universality in Automata Networks
Mart\'in R\'ios-Wilson, Guillaume Theyssier (I2M, I2M)

TL;DR
This paper develops a theory of intrinsic simulations and universality for automata networks, linking these concepts to complexity and decision problems, and introduces a new proof technique for symmetric networks.
Contribution
It introduces a formal framework for intrinsic universality in automata networks and a novel glueing technique for analyzing complex orbits in symmetric networks.
Findings
Intrinsic universality implies hardness of prediction and reachability problems.
Orthogonality of decision problem complexities in automata networks.
The 'game of life' networks are strongly universal.
Abstract
An automata network (AN) is a finite graph where each node holds a state from a finite alphabet and is equipped with a local map defining the evolution of the state of the node depending on its neighbors. They are studied both from the dynamical and the computational complexity point of view. Inspired from well-established notions in the context of cellular automata, we develop a theory of intrinsic simulations and universality for families of automata networks. We establish many consequences of intrinsic universality in terms of complexity of orbits (periods of attractors, transients, etc) as well as hardness of the standard well-studied decision problems for automata networks (short/long term prediction, reachability, etc). In the way, we prove orthogonality results for these problems: the hardness of a single one does not imply hardness of the others, while intrinsic universality…
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Taxonomy
TopicsCellular Automata and Applications · Stochastic processes and statistical mechanics
