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Boolean networks have been used in a variety of settings, as models for general complex systems as well as models of specific systems in diverse fields, such as biology, engineering, and computer science. Traditionally, their properties as…

Dynamical Systems · Mathematics 2024-02-02 Matthew Wheeler , Claus Kadelka , Alan Veliz-Cuba , David Murrugarra , Reinhard Laubenbacher

Found in varied contexts from neurons to ants to fish, binary decision-making is one of the simplest forms of collective computation. In this process, information collected by individuals about an uncertain environment is accumulated to…

Neurons and Cognition · Quantitative Biology 2019-03-26 Bryan C. Daniels , Pawel Romanczuk

Motivated by an attempt to develop a method for solving initial value problems in a class of one dimensional periodic cellular automata (CA) associated with crystal bases and soliton equations, we consider a generalization of a simple…

Exactly Solvable and Integrable Systems · Physics 2009-02-10 Taichiro Takagi

Nonlinear complexity is an important measure for assessing the randomness of sequences. In this paper we investigate how circular shifts affect the nonlinear complexities of finite-length binary sequences and then reveal a more explicit…

Information Theory · Computer Science 2024-04-26 Qin Yuan , Chunlei Li , Xiangyong Zeng , Tor Helleseth , Debiao He

In this work, we begin to investigate the possibility of training a deep neural network on the task of binary code understanding. Specifically, the network would take, as input, features derived directly from binaries and output English…

Machine Learning · Computer Science 2024-05-01 Alexander Interrante-Grant , Andy Davis , Heather Preslier , Tim Leek

A novel, information-based classification of elementary cellular automata is proposed that circumvents the problems associated with isolating whether complexity is in fact intrinsic to a dynamical rule, or if it arises merely as a product…

Computational Complexity · Computer Science 2017-03-01 Enrico Borriello , Sara Imari Walker

It has been shown that uniform as well as non-uniform cellular automata (CA) can be evolved to perform certain computational tasks. Random Boolean networks are a generalization of two-state cellular automata, where the interconnection…

Disordered Systems and Neural Networks · Physics 2007-05-23 Bertrand Mesot , Christof Teuscher

A conjunctive Boolean network (CBN) is a finite state dynamical system, whose variables take values from a binary set, and the value update rule for each variable is a Boolean function consisting only of logic AND operations. We investigate…

Dynamical Systems · Mathematics 2019-07-11 Xudong Chen , Zuguang Gao , Tamer Başar

This study focuses on an extended model of a standard cellular automaton (CA) that includes an extra index consisting of a radius that defines a perception area for each cell in addition to the radius defined by the CA rule. Extended…

Computational Complexity · Computer Science 2015-12-22 Yoshihiko Kayama

Neural Cellular Automata (NCA) models have shown remarkable capacity for pattern formation and complex global behaviors stemming from local coordination. However, in the original implementation of NCA, cells are incapable of adjusting their…

Neural and Evolutionary Computing · Computer Science 2023-05-18 Ettore Randazzo , Alexander Mordvintsev , Craig Fouts

In this paper we study the macroscopic conduction properties of large but finite binary networks with conducting bonds. By taking a combination of a spectral and an averaging based approach we derive asymptotic formulae for the conduction…

Disordered Systems and Neural Networks · Physics 2015-06-04 D. P. Almond , C. J. Budd , M. A. Freitag , G. W. Hunt , N. J. McCullen , N. D. Smith

We introduce several concepts such as prime and composite rule, tools and methods for causal composition and decomposition. We discover and prove new universality results in ECA, namely, that the Boolean composition of ECA rules 51 and 118,…

Cellular Automata and Lattice Gases · Physics 2018-02-27 Jürgen Riedel , Hector Zenil

The emergence of complex behaviors in cellular automata is an area that has been widely developed in recent years with the intention to generate and analyze automata that produce space-moving patterns or gliders that interact in a periodic…

Exact solutions for the learning problem of autoassociative networks with binary couplings are determined by a new method. The use of a branch-and-bound algorithm leads to a substantial saving of computational time compared with complete…

Disordered Systems and Neural Networks · Physics 2009-10-30 G. Milde , S. Kobe

Causal relationship recognition is a fundamental operation in neural networks aimed at learning behavior, action planning, and inferring external world dynamics. This operation is particularly crucial for reinforcement learning (RL). In the…

Neural and Evolutionary Computing · Computer Science 2023-09-18 Mikhail Kiselev , Denis Larionov , Andrey Urusov

We rigorously prove a form of disorder-resistance for a class of one-dimensional cellular automaton rules, including some that arise as boundary dynamics of two-dimensional solidification rules. Specifically, when started from a random…

Probability · Mathematics 2015-09-30 Janko Gravner , Alexander E. Holroyd

Normal networks are an important class of phylogenetic networks that have compelling mathematical properties which align with intuition about inference from genetic data. While tools enabling widespread use of phylogenetic networks in the…

Combinatorics · Mathematics 2025-12-16 Andrew Francis , Charles Semple

Elementary cellular automata (ECA) are converted into multiplicative versions by using permuted n-dim Galois fields and octonion multiplication tables as binary pointers to each rule's Wolfram code truth table. This enables an extension of…

Cellular Automata and Lattice Gases · Physics 2025-02-20 Daniel McKinley

Biological rhythms are generated by pacemaker organs, such as the heart pacemaker organ (the sinoatrial node) and the master clock of the circadian rhythms (the suprachiasmatic nucleus), which are composed of a network of autonomously…

Cell Behavior · Quantitative Biology 2016-08-23 Hiroshi Kori , Yoji Kawamura , Naoki Masuda

The cell cycle is a tightly controlled process, yet its underlying genetic network shows marked differences across species. Which of the associated structural features follow solely from the ability to impose the appropriate gene expression…

Molecular Networks · Quantitative Biology 2015-06-12 M. Zagorski , A. Krzywicki , O. C. Martin