๐ฎ
๐ฎ
The Ethereal
(Biased) Majority Rule Cellular Automata
November 24, 2017 ยท The Ethereal ยท ๐ arXiv.org
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Bernd Gรคrtner, Ahad N. Zehmakan
arXiv ID
1711.10920
Category
cs.FL: Formal Languages
Cross-listed
cs.DS,
nlin.CG
Citations
10
Venue
arXiv.org
Last Checked
1 month ago
Abstract
Consider a graph $G=(V,E)$ and a random initial vertex-coloring, where each vertex is blue independently with probability $p_{b}$, and red with probability $p_r=1-p_b$. In each step, all vertices change their current color synchronously to the most frequent color in their neighborhood and in case of a tie, a vertex conserves its current color; this model is called majority model. If in case of a tie a vertex always chooses blue color, it is called biased majority model. We are interested in the behavior of these deterministic processes, especially in a two-dimensional torus (i.e., cellular automaton with (biased) majority rule). In the present paper, as a main result we prove both majority and biased majority cellular automata exhibit a threshold behavior with two phase transitions. More precisely, it is shown that for a two-dimensional torus $T_{n,n}$, there are two thresholds $0\leq p_1, p_2\leq 1$ such that $p_b \ll p_1$, $p_1 \ll p_b \ll p_2$, and $p_2 \ll p_b$ result in monochromatic configuration by red, stable coexistence of both colors, and monochromatic configuration by blue, respectively in $\mathcal{O}(n^2)$ number of steps
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
๐ Similar Papers
In the same crypt โ Formal Languages
๐ฎ
๐ฎ
The Ethereal
Supervisor Synthesis to Thwart Cyber Attack with Bounded Sensor Reading Alterations
๐ฎ
๐ฎ
The Ethereal
An Abstraction-Based Framework for Neural Network Verification
๐ฎ
๐ฎ
The Ethereal
Recurrent Neural Networks as Weighted Language Recognizers
๐ฎ
๐ฎ
The Ethereal
TeSSLa: Temporal Stream-based Specification Language
๐ฎ
๐ฎ
The Ethereal