PSPACE-Completeness of Majority Automata Networks
Eric Goles, Pedro Montealegre, Ville Salo, Ilkka T\"orm\"a
TL;DR
This paper proves that predicting state changes in majority automata networks under block sequential updates is a PSPACE-complete problem, highlighting the computational complexity of analyzing such systems.
Contribution
It establishes the PSPACE-completeness of the prediction problem for majority automata networks with block sequential updates, a novel complexity result.
Findings
Prediction problem is PSPACE-complete.
Complexity holds for block sequential updating scheme.
Advances understanding of computational difficulty in automata network dynamics.
Abstract
We study the dynamics of majority automata networks when the vertices are updated according to a block sequential updating scheme. In particular, we show that the complexity of the problem of predicting an eventual state change in some vertex, given an initial configuration, is PSPACE-complete.
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Taxonomy
TopicsCellular Automata and Applications · semigroups and automata theory · Complex Network Analysis Techniques