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This paper details a method for optimising the size of Boolean automata networks in order to compute their attractors under the parallel update schedule. This method relies on the formalism of modules introduced recently that allows for…

Logic in Computer Science · Computer Science 2020-07-21 Kévin Perrot , Pacôme Perrotin , Sylvain Sené

A model of Boolean game with only one free parameter $p$ that denotes the strength of herd behavior is proposed where each agent acts according to the information obtained from his neighbors in network and those in the minority are…

Statistical Mechanics · Physics 2007-05-23 Tao Zhou , Bing-Hong Wang , Pei-Ling Zhou , Chun-Xia Yang , Jun Liu

The recently measured yeast transcriptional network is analyzed in terms of simplified Boolean network models, with the aim of determining feasible rule structures, given the requirement of stable solutions of the generated Boolean…

Molecular Networks · Quantitative Biology 2009-11-10 Stuart Kauffman , Carsten Peterson , Björn Samuelsson , Carl Troein

We study the intrinsic properties of attractors in the Boolean dynamics in complex network with scale-free topology, comparing with those of the so-called random Kauffman networks. We have numerically investigated the frozen and relevant…

Disordered Systems and Neural Networks · Physics 2007-08-21 Shu-ichi Kinoshita , Kazumoto Iguchi , Hiroaki S. Yamada

A Boolean network is a discrete dynamical system operating on vectors of Boolean variables. The action of a Boolean network can be conveniently expressed as a system of Boolean update functions, computing the new values for each component…

Formal Languages and Automata Theory · Computer Science 2023-03-02 Artiom Alhazov , Vincent Ferrari-Dominguez , Rudolf Freund , Nicolas Glade , Sergiu Ivanov

Interaction graphs provide an important qualitative modeling approach for System Biology. This paper presents a novel approach for construction of interaction graph with the help of Boolean function decomposition. Each decomposition part…

Systems and Control · Computer Science 2014-09-26 Jayanta Kumar Das , Ranjeet Kumar Rout , Pabitra Pal Choudhury

Emergence of robustness in biological networks is a paramount feature of evolving organisms, but a study of this property in vivo, for any level of representation such as Genetic, Metabolic, or Neuronal Networks, is a very hard challenge.…

Molecular Networks · Quantitative Biology 2012-10-18 Vitor H. P. Louzada , Fabrício M. Lopes , Ronaldo F. Hashimoto

A longstanding idea in the literature on human cooperation is that cooperation should be reinforced when conditional cooperators are more likely to interact. In the context of social networks, this idea implies that cooperation should fare…

Computer Science and Game Theory · Computer Science 2015-05-19 Siddharth Suri , Duncan J. Watts

Neural networks are dynamical systems that compute with their dynamics. One example is the Hopfield model, forming an associative memory which stores patterns as global attractors of the network dynamics. From studies of dynamical networks…

Emerging Technologies · Computer Science 2021-12-13 Lorenz Baumgarten , Stefan Bornholdt

We present results from numerical studies of supervised learning operations in recurrent networks considered as graphs, leading from a given set of input conditions to predetermined outputs. Graphs that have optimized their output for…

Adaptation and Self-Organizing Systems · Physics 2007-05-23 H. Atmanspacher , T. Filk

We provide conditions on the coupling function such that a system of 4 globally coupled identical oscillators has chaotic attractors, a pair of Lorenz attractors or a 4-winged analogue of the Lorenz attractor. The attractors emerge near the…

Chaotic Dynamics · Physics 2024-08-14 Efrosiniia Karatetskaia , Alexey Kazakov , Klim Safonov , Dmitry Turaev

We provide the first classification of different types of Random Boolean Networks (RBNs). We study the differences of RBNs depending on the degree of synchronicity and determinism of their updating scheme. For doing so, we first define…

Computational Complexity · Computer Science 2007-05-23 Carlos Gershenson

Strength of attractor is studied by the return rate to itself after perturbations, for a multi-attractor state of a globally coupled map. It is found that fragile (Milnor) attractors have a large basin volume at the partially ordered phase.…

chao-dyn · Physics 2009-10-31 Kunihiko Kaneko

We describe systems using Kauffman and similar networks. They are directed funct ioning networks consisting of finite number of nodes with finite number of discr ete states evaluated in synchronous mode of discrete time. In this paper we…

Disordered Systems and Neural Networks · Physics 2009-11-13 Andrzej Gecow

We study a condition of favoring cooperation in a Prisoner's Dilemma game on complex networks. There are two kinds of players: cooperators and defectors. Cooperators pay a benefit b to their neighbors at a cost c, whereas defectors only…

Physics and Society · Physics 2019-11-20 Tomohiko Konno

We consider networks formed from two populations of identical oscillators, with uniform strength all-to-all coupling within populations, and also between populations, with a different strength. Such systems are known to support chimera…

Chaotic Dynamics · Physics 2019-08-28 Carlo R. Laing

We consider a class of stochastic dynamical networks whose governing dynamics can be modeled using a coupling function. It is shown that the dynamics of such networks can generate geometrically ergodic trajectories under some reasonable…

Systems and Control · Electrical Eng. & Systems 2022-11-22 Arash Amini , Qiyu Sun , Nader Motee

We study a Life-like cellular automaton rule $B2/S2345$ where a cell in state `0' takes state `1' if it has exactly two neighbors in state `1' and the cell remains in the state `1' if it has between two and five neighbors in state `1.' This…

Pattern Formation and Solitons · Physics 2011-06-16 Genaro J. Martinez , Andrew Adamatzky , Kenichi Morita , Maurice Margenstern

GANs have two competing modules: the generator module is trained to generate new examples, and the discriminator module is trained to discriminate real examples from generated examples. The training procedure of GAN is modeled as a finitely…

Machine Learning · Computer Science 2022-09-29 Ch. Sobhan Babu , Ravindra Guravannavar , Arvind Hulgeri

Random Boolean Network has been used to find out regulation patterns of genes in organism. his approach is very interesting to use in a game such as N Person PD. Here we assume that action is influenced by input in the form of choices of…

Disordered Systems and Neural Networks · Physics 2007-05-23 Hokky Situngkir , Deni Khanafiah