arXiv subjects

Franco Bagnoli

Publications and source records attributed to Franco Bagnoli.

At least 73 records · Page 4Linked to original sources

arXiv2012

Cognitive network structure: an experimental study

In this paper we present first experimental results about a small group of people exchanging private and public messages in a virtual community. Our goal is the study of the cognitive network that emerges during a chat seance. We used the Derrida coefficient and the triangle structure under the working assumption that moods and perceived mutual affinity can produce results complementary to a full semantic analysis. The most outstanding outcome is the difference between the network obtained considering publicly exchanged messages and the one considering only privately exchanged messages: in the former case, the network is very homogeneous, in the sense that each individual interacts in the same way with all the participants, whilst in the latter the interactions among different agents are very heterogeneous, and are based on "the enemy of my enemy is my friend" strategy. Finally a recent characterization of the triangular cliques has been considered in order to describe the intimate structure of the network. Experimental results confirm recent theoretical studies indicating that certain 3-vertex structures can be used as indicators for the network aging and some relevant dynamical features.

physics.soc-ph↗

arXiv2012

Community-detection cellular automata with local and long-range connectivity

We explore a community-detection cellular automata algorithm inspired by human heuristics, based on information diffusion and a non-linear processing phase with a dynamics inspired by human heuristics. The main point of the methods is that of furnishing different "views" of the clustering levels from an individual point of view. We apply the method to networks with local connectivity and long-range rewiring.

nlin.CG↗

arXiv2012

Control of cellular automata

We study the problem of master-slave synchronization and control of totalistic cellular automata (CA) by putting a fraction of sites of the slave equal to those of the master and finding the distance between both as a function of this fraction. We present three control strategies that exploit local information about the CA, mainly, the number of nonzero Boolean derivatives. When no local information is used, we speak of synchronization. We find the critical properties of control and discuss the best control strategy compared with synchronization.

nlin.CG↗

arXiv2011

Fisica e fumetti: Paperone ed il deposito sotterraneo

I fumetti, come i film, spesso utilizzano idee scientifiche "fantasiose". Non ci riferiamo qui alla violazione implicita delle leggi della fisica, cosa permessa in un mondo di fantasia, quanto piuttosto all'uso di spiegazioni fisiche errate che vengono usate in buona fede perché a riflettono convinzioni molto diffuse, ma sbagliate, sull'interpretazione di fenomeni a partire dai principi fisici. D'altra parte questi errori possono servire a illustrare la corretta applicazione della fisica in una maniera molto più accattivante rispetto alla modalitá tradizionale di presentazione. Analizziamo qui l'avventura Paperone ed il deposito sotterraneo di Pezzin e Cavezzano. ----- Comics and cartoon movies sometimes exploit fictitious scientific ideas. It is often the case that these ideas, althought wrong, actually reflect the popular vision of some natural phenomenon. We do not refer here to the implicit violation of physical laws in fictions, a practice allowed by the underlining "poetic licence" of comics. However, sometimes wrong scientific "explanations" are proposed, and those may be accepted by the public without further inspection. On the other hand, these errors may be a good starting point for a didactic illustration of physical principles. We analyse here the comics Paperone ed il deposito sotterraneo (Uncle Scrooge and the underground money bin) by Perrin e Cavezzano.

physics.pop-ph↗

arXiv2011

Sipping Science in a Café

We present here the European project SciCafé - networking of science cafés in Europe and neighboring countries, and the contributions of the CSDC-Caffè Scienza partner in Florence, Itay.

physics.pop-ph↗

arXiv2010

Decisional Processes with Boolean Neural Network: the Emergence of Mental Schemes

Human decisional processes result from the employment of selected quantities of relevant information, generally synthesized from environmental incoming data and stored memories. Their main goal is the production of an appropriate and adaptive response to a cognitive or behavioral task. Different strategies of response production can be adopted, among which haphazard trials, formation of mental schemes and heuristics. In this paper, we propose a model of Boolean neural network that incorporates these strategies by recurring to global optimization strategies during the learning session. The model characterizes as well the passage from an unstructured/chaotic attractor neural network typical of data-driven processes to a faster one, forward-only and representative of schema-driven processes. Moreover, a simplified version of the Iowa Gambling Task (IGT) is introduced in order to test the model. Our results match with experimental data and point out some relevant knowledge coming from psychological domain.

cs.AI↗

arXiv2010

Noise and nonlinearities in high-throughput data

High-throughput data analyses are becoming common in biology, communications, economics and sociology. The vast amounts of data are usually represented in the form of matrices and can be considered as knowledge networks. Spectra-based approaches have proved useful in extracting hidden information within such networks and for estimating missing data, but these methods are based essentially on linear assumptions. The physical models of matching, when applicable, often suggest non-linear mechanisms, that may sometimes be identified as noise. The use of non-linear models in data analysis, however, may require the introduction of many parameters, which lowers the statistical weight of the model. According to the quality of data, a simpler linear analysis may be more convenient than more complex approaches. In this paper, we show how a simple non-parametric Bayesian model may be used to explore the role of non-linearities and noise in synthetic and experimental data sets.

q-bio.QM↗

arXiv2009

Smallworld bifurcations in an opinion model

We study a cellular automaton opinion formation model of Ising type, with antiferromagnetic pair interactions modeling anticonformism, and ferromagnetic plaquette terms modeling the social norm constraints. For a sufficiently large connectivity, the mean-field equation for the average magnetization (opinion density) is chaotic. This "chaoticity" would imply irregular coherent oscillations of the whole society, that may eventually lead to a sudden jump into an absorbing state, if present. However, simulations on regular one-dimensional lattices show a different scenario: local patches may oscillate following the mean-field description, but these oscillations are not correlated spatially, so the average magnetization fluctuates around zero (average opinion near one half). The system is chaotic, but in a microscopic sense where local fluctuations tend to compensate each other. By varying the long-range rewiring of links, we trigger a small-world effect. We observe a bifurcation diagram for the magnetization, with period doubling cascades ending in a chaotic phase. As far as we know, this is the first observation of a small-world induced bifurcation diagram. The social implications of this transition are also interesting. In the presence of strong "anticonformistic" (or "antinorm") behavior, efforts for promoting social homogenization may trigger violent oscillations.

physics.soc-ph↗

arXiv2009

From Newton to Cellular Automata

I outline a possible logical path from the formulation of physics of classical mechanics to "abstract" systems like cellular automata. The goal of this article is that of illustrating why physicists often study extremely simplified models, instead of just numerically integrating the fundamental equations of physics. This exposition is obviously only partial and based on my expertise and my interests.

physics.pop-ph↗

arXiv2009

Evolutionary models for simple biosystems

The concept of evolutionary development of structures constituted a \emph{real} revolution in biology: it was possible to understand how the very complex structures of life can arise in an out-of-equilibrium system. The investigation of such systems has shown that indeed, systems under a flux of energy or matter can self-organize into complex patterns, think for instance to Rayleigh-Bernard convection, Liesegang rings, patterns formed by granular systems under shear. Following this line, one could characterize life as a state of matter, characterized by the slow, continuous process that we call evolution. In this paper we try to identify the organizational level of life, that spans several orders of magnitude from the elementary constituents to whole ecosystems. Although similar structures can be found in other contexts like ideas (memes) in neural systems and self-replicating elements (computer viruses, worms, etc.) in computer systems, we shall concentrate on biological evolutionary structure, and try to put into evidence the role and the emergence of network structure in such systems.

q-bio.PE↗

arXiv2009

Finite Size Effects for the Ising Model on Random Graphs with Varying Dilution

We investigate the finite size corrections to the equilibrium magnetization of an Ising model on a random graph with $N$ nodes and $N^γ$ edges, with $1 < γ\leq 2$. By conveniently rescaling the coupling constant, the free energy is made extensive. As expected, the system displays a phase transition of the mean-field type for all the considered values of $γ$ at the transition temperature of the fully connected Curie-Weiss model. Finite size corrections are investigated for different values of the parameter $γ$, using two different approaches: a replica-based finite $N$ expansion, and a cavity method. Numerical simulations are compared with theoretical predictions. The cavity based analysis is shown to agree better with numerics.

cond-mat.stat-mech↗

arXiv2009

Synchronization and control of cellular automata

The control of chaotic systems implies inducing an unpredictable system to follow a desired trajectory using the smallest "force". In low-dimensional continuous systems, one method is that of reconstructing the tangent space, so that the control may be concentrated on the most expanding directions. This scheme is hard to follow for high-dimensional (extended) systems. This is particularly true for extended systems that exhibit stable chaos, that is, systems which are not chaotic in the usual sense, but are unpredictable for finite perturbations. Prototypical of this class are cellular automata, aka completely discrete dynamical systems. Although usual indicators of chaoticity such as the maximum Lyapunov exponent may be defined for such systems, we show that the usual approach may lead to counter intuitive results, and that it is possible to exploit the characteristics of the system in order to reduce the distance between two replicas with less control.

nlin.CG↗

arXiv2009

Thermodynamic Entropy and Chaos in a Discrete Hydrodynamical System

We show that the thermodynamic entropy density is proportional to the largest Lyapunov ex- ponent (LLE) of a discrete hydrodynamical system, a deterministic two-dimensional lattice gas automaton. The definition of the LLE for cellular automata is based on the concept of Boolean derivatives and is formally equivalent to that of continuous dynamical systems. This relation is jus- tified using a Markovian model. In an irreversible process with an initial density difference between both halves of the system, we find that Boltzmann's H function is linearly related to the expansion factor of the LLE, although the latter is more sensitive to the presence of traveling waves.

cond-mat.stat-mech↗

arXiv2008

Birth and Death in a Continuous Opinion Dynamics Model. The consensus case

We here discuss the process of opinion formation in an open community where agents are made to interact and consequently update their beliefs. New actors (birth) are assumed to replace individuals that abandon the community (deaths). This dynamics is simulated in the framework of a simplified model that accounts for mutual affinity between agents. A rich phenomenology is presented and discussed with reference to the original (closed group) setting. Numerical findings are supported by analytical calculations.

physics.soc-ph↗

arXiv2008

Human Heuristics for Autonomous Agents

We investigate the problem of autonomous agents processing pieces of information that may be corrupted (tainted). Agents have the option of contacting a central database for a reliable check of the status of the message, but this procedure is costly and therefore should be used with parsimony. Agents have to evaluate the risk of being infected, and decide if and when communicating partners are affordable. Trustability is implemented as a personal (one-to-one) record of past contacts among agents, and as a mean-field monitoring of the level of message corruption. Moreover, this information is slowly forgotten in time, so that at the end everybody is checked against the database. We explore the behavior of a homogeneous system in the case of a fixed pool of spreaders of corrupted messages, and in the case of spontaneous appearance of corrupted messages.

cs.MA↗

arXiv2007

Opinion Dynamics in an Open Community

physics.soc-ph↗

arXiv2007

A Biologically Inspired Classifier

We present a method for measuring the distance among records based on the correlations of data stored in the corresponding database entries. The original method (F. Bagnoli, A. Berrones and F. Franci. Physica A 332 (2004) 509-518) was formulated in the context of opinion formation. The opinions expressed over a set of topic originate a ``knowledge network'' among individuals, where two individuals are nearer the more similar their expressed opinions are. Assuming that individuals' opinions are stored in a database, the authors show that it is possible to anticipate an opinion using the correlations in the database. This corresponds to approximating the overlap between the tastes of two individuals with the correlations of their expressed opinions. In this paper we extend this model to nonlinear matching functions, inspired by biological problems such as microarray (probe-sample pairing). We investigate numerically the error between the correlation and the overlap matrix for eight sequences of reference with random probes. Results show that this method is particularly robust for detecting similarities in the presence of translocations.

cs.DB↗

arXiv2007

Risk perception in epidemic modeling

We investigate the effects of risk perception in a simple model of epidemic spreading. We assume that the perception of the risk of being infected depends on the fraction of neighbors that are ill. The effect of this factor is to decrease the infectivity, that therefore becomes a dynamical component of the model. We study the problem in the mean-field approximation and by numerical simulations for regular, random and scale-free networks. We show that for homogeneous and random networks, there is always a value of perception that stops the epidemics. In the ``worst-case'' scenario of a scale-free network with diverging input connectivity, a linear perception cannot stop the epidemics; however we show that a non-linear increase of the perception risk may lead to the extinction of the disease. This transition is discontinuous, and is not predicted by the mean-field analysis.

q-bio.PE↗