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Interactive consistency is the problem in which n nodes, where up to t may be byzantine, each with its own private value, run an algorithm that allows all non-faulty nodes to infer the values of each other node. This problem is relevant to…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-07-28 Panos Diamantopoulos , Stathis Maneas , Christos Patsonakis , Nikos Chondros , Mema Roussopoulos

Boolean networks, inspired by gene regulatory networks, were developed to understand the complex behaviors observed in biological systems, with network attractors corresponding to biological phenotypes or cell types. In this article, we…

Molecular Networks · Quantitative Biology 2025-11-25 Venkata Sai Narayana Bavisetty , Matthew Wheeler , Reinhard Laubenbacher , Claus Kadelka

Asynchronous Boolean networks are a type of discrete dynamical system in which each variable can take one of two states, and a single variable state is updated in each time step according to pre-selected rules. Boolean networks are popular…

Molecular Networks · Quantitative Biology 2024-10-08 Samuel Pastva , Kyu Hyong Park , Ondrej Huvar , Jordan C Rozum , Reka Albert

An automata network is a finite graph where each node holds a state from some finite alphabet and is equipped with an update function that changes its state according to the configuration of neighboring states. More concisely, it is given…

Computational Complexity · Computer Science 2020-04-28 Florian Bridoux , Maximilien Gadouleau , Guillaume Theyssier

Boolean networks are a popular modeling framework in computational biology to capture the dynamics of molecular networks, such as gene regulatory networks. It has been observed that many published models of such networks are defined by…

Molecular Networks · Quantitative Biology 2019-12-06 Elijah Paul , Gleb Pogudin , William Qin , Reinhard Laubenbacher

The paper addresses the synchronization of multi-agent systems with continuous-time dynamics interacting through a very general class of monotonic continuous signal functions that covers estimation biases, approximation of discrete…

Systems and Control · Electrical Eng. & Systems 2025-03-14 Anthony Couthures , Vineeth S. Varma , Samson Lasaulce , Irinel-Constantin Morarescu

In this work, we develop a method to identify continuous-time nonlinear networked dynamics via the Koopman operator framework. The proposed technique consists of two steps: the first step identifies the neighbors of each node, and the…

Systems and Control · Electrical Eng. & Systems 2024-12-25 Ramachandran Anantharaman , Alexandre Mauroy

We consider complete synchronization of identical maps coupled through a general interaction function and in a general network topology where the edges may be directed and may carry both positive and negative weights. We define mixed…

Chaotic Dynamics · Physics 2009-09-15 Frank Bauer , Fatihcan M. Atay , Juergen Jost

Boolean networks at the critical point have been a matter of debate for many years as, e.g., scaling of number of attractor with system size. Recently it was found that this number scales superpolynomially with system size, contrary to a…

Disordered Systems and Neural Networks · Physics 2009-11-10 Konstantin Klemm , Stefan Bornholdt

Imitation is widely observed in populations of decision-making agents. Using our recent convergence results for asynchronous imitation dynamics on networks, we consider how such networks can be efficiently driven to a desired equilibrium…

Computer Science and Game Theory · Computer Science 2017-04-17 James Riehl , Pouria Ramazi , Ming Cao

A well-known theorem by Fran\c{c}ois Robert expresses the degenerated character of a synchronous Boolean finite dynamical system, in the case where the associated regulatory graph does not contain any circuit: all states of the system go…

Dynamical Systems · Mathematics 2025-02-20 Brigitte Mossé , Sasha Pignol , Elisabeth Remy

In this paper we propose a decentralized sensor network scheme capable to reach a globally optimum maximum likelihood (ML) estimate through self-synchronization of nonlinearly coupled dynamical systems. Each node of the network is composed…

Distributed, Parallel, and Cluster Computing · Computer Science 2009-11-11 Sergio Barbarossa , Gesualdo Scutari

Boolean networks, first developed in the late 1960s as a tool for studying complex disordered dynamical systems, consist of nodes governed by Boolean functions whose evolution is entirely deterministic in that the state of the network at a…

Quantum Physics · Physics 2023-03-02 Ian T. Durham

Stability is an important characteristic of network models that has implications for other desirable aspects such as controllability. The stability of a Boolean network depends on various factors, such as the topology of its wiring diagram…

Chaotic Dynamics · Physics 2024-07-09 Karthik Chandrasekhar , Claus Kadelka , Reinhard Laubenbacher , David Murrugarra

We establish new separations between the power of monotone and general (non-monotone) Boolean circuits: - For every $k \geq 1$, there is a monotone function in ${\sf AC^0}$ that requires monotone circuits of depth $\Omega(\log^k n)$. This…

Computational Complexity · Computer Science 2023-05-12 Bruno P. Cavalar , Igor C. Oliveira

A Boolean network (BN) with $n$ components is a discrete dynamical system described by the successive iterations of a function $f:\{0,1\}^n \to \{0,1\}^n$. This model finds applications in biology, where fixed points play a central role.…

Combinatorics · Mathematics 2022-02-10 Florian Bridoux , Amélia Durbec , Kévin Perrot , Adrien Richard

We consider a model recently proposed by Chatterjee and Durrett [CD2011] as an "annealed approximation" of boolean networks, which are a class of cellular automata on a random graph, as defined by S. Kauffman [K69]. The starting point is a…

Probability · Mathematics 2012-12-06 Thomas Mountford , Daniel Valesin

The theory of monotone dynamical systems has been found very useful in the modeling of some gene, protein, and signaling networks. In monotone systems, every net feedback loop is positive. On the other hand, negative feedback loops are…

Dynamical Systems · Mathematics 2009-11-13 Liming Wang , Eduardo Sontag

Random Boolean networks, the Kauffman model, are revisited by means of a novel decimation algorithm, which reduces the networks to their dynamical cores. The average size of the removed part, the stable core, grows approximately linearly…

Statistical Mechanics · Physics 2009-11-07 S. Bilke , F. Sjunnesson

We introduce a simple network formation model for social networks. Agents are nodes, connecting to another agent by building a directed edge (or accepting a connection from another agent) has a cost, and reaching (or being reached by) other…

Social and Information Networks · Computer Science 2016-04-22 L. Elisa Celis , Aida Sadat Mousavifar