Search arXiv⌕ Search
Home/Archive/arXiv

arXiv · 0704.2533

Multi-Agent Approach to the Self-Organization of Networks

Frank Schweitzer
View original source ↗Read source document ↗Export metadata ↓

Abstract

Is it possible to link a set of nodes without using preexisting positional information or any kind of long-range attraction of the nodes? Can the process of generating positional information, i.e. the detection of ``unknown'' nodes and the estabishment of chemical gradients, \emph{and} the process of network formation, i.e. the establishment of links between nodes, occur in parallel, on a comparable time scale, as a process of co-evolution? The paper discusses a model where the generation of relevant information for establishing the links between nodes results from the interaction of many \emph{agents}, i.e. subunits of the system that are capable of performing some activities. Their collective interaction is based on (indirect) communication, which also includes memory effects and the dissemination of information in the system. The relevant (``pragmatic'') information that leads to the establishment of the links then emerges from an evolutionary interplay of selection and reamplification.

Explore related subjects

nlin.AOphysics.bio-phq-bio.QM

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Frank Schweitzer. 2007-04-19. Multi-Agent Approach to the Self-Organization of Networks. https://arxiv.org/abs/0704.2533

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

arXiv2026

Bend-Twist Coupling and its Design from Geometrical Constraints in Double Stranded DNA

Under the strongly coupled condition in the adiabatic environment, the fast dynamics originated from the boundary of the target system, governed by target and environmental Hamiltonians, is closely related to the energy gain and loss between the two distinct Hamiltonians. Leveraging this restriction, we investigate how the bi-Hamiltonian condition regulates stochastic dynamics to shape the macroscopic behavior of a semiflexible polymer, analyzing the intrinsic drift from the Dzhanibekov effect and a diffusion process derived from the Smoluchowski equation within a coarse-grained system. The Smoluchowski picture, defined within the framework of stochastic thermodynamics, justifies the usage of a diffusion process in the canonical equations of motion replacing the memory effect defined in the non-Markovian regime. The results of the numerical experiments on the collision, including a previous study on free thermal vibration replicated using the same framework, confirm that heat diffusion process compensates the precision in both equilibrium and far-from-equilibrium states.

nlin.AO↗
arXiv2026

Waveform proportionality and Taylor's law in networks of Lorenz systems

Taylor's law (TL), a power-law relationship between the mean and variance of a quantity, has been observed across diverse scientific disciplines. Despite its ubiquity, the underlying mechanisms responsible for TL have not yet been fully elucidated. In particular, the frequent empirical observation of TL with an exponent 2 warrants further investigation. In a previous study, we hypothesized that synchronization contributes to the emergence of TL with an exponent 2. To validate this hypothesis, we employed coupled oscillator models, with each oscillator described by a distinct dynamical system: a food chain model, the Rössler system, the Brusselator, and the Lorenz system. Our analytical and numerical results demonstrated that strong coupling leads to a form of synchronization wherein time series become proportional to each other, resulting in TL with an exponent 2. Here, we extend our previous findings for the coupled Lorenz system and provide detailed calculations. We analytically and numerically show that, under strong coupling, waveform proportionality and TL with an exponent 2 emerge for some variables in the globally coupled original, generalized, and hyperchaotic Lorenz systems. Furthermore, we derive a condition under which these properties hold for the original Lorenz system on networks. We then numerically confirm that when heterogeneous oscillators are randomly distributed within the network, waveform proportionality and TL with an exponent 2 emerge across several representative network structures, such as a two-dimensional lattice, random networks, and scale-free networks.

nlin.AO↗
arXiv2026

Recovery Random Walks for Extreme Events on Complex Networks

Extreme events are widely studied within simple random walk frameworks, where their probability is determined by the network structure and stationary walker distribution. Here, we propose a recovery random walk (RRW) model in which extreme events temporally `freeze' the nodes where they occur for a fixed duration $Δ$ ($Δ=0$ recovers the original model), trapping walkers and reducing the effective mobile population, thereby making the model more practical. We derive a first-principles description of this feedback and a delayed differential equation for the frozen-node fraction. This finite freezing produces an initial overshoot, followed by damped oscillatory relaxation to a steady state for the fraction of the frozen nodes. We find that freezing suppresses extreme event probability while preserving its degree dependence dynamics, and suppresses the EE frequency. Further, the analytical prediction for the fraction of the frozen nodes agrees closely with simulations. This model closely reflects real-world scenarios, yielding more practical EE statistics.

nlin.AO↗