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As one of the main subjects of investigation in data science, network science has been demonstrated a wide range of applications to real-world networks analysis and modeling. For example, the pervasive presence of structural or topological…

Logic in Computer Science · Computer Science 2020-09-28 Felipe S. Abrahão , Klaus Wehmuth , Artur Ziviani

Transfer learning is a machine learning paradigm where the knowledge from one task is utilized to resolve the problem in a related task. On the one hand, it is conceivable that knowledge from one task could be useful for solving a related…

Machine Learning · Computer Science 2021-05-05 Xuetong Wu , Jonathan H. Manton , Uwe Aickelin , Jingge Zhu

A population protocol describes a set of state change rules for a population of $n$ indistinguishable finite-state agents (automata), undergoing random pairwise interactions. Within this very basic framework, it is possible to resolve a…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-04-19 Adrian Kosowski , Przemysław Uznański

Contact processes (CP's) with particle creation requiring a minimal neighborhood (restrictive or threshold CP's) present a novel sort of discontinuous absorbing transitions, that revealed itself robust under the inclusion of different…

Statistical Mechanics · Physics 2016-03-30 Salete Pianegonda , C. E. Fiore

The percolation phase transition in complex network systems attracts much attention and has numerous applications in various research fields. Finite size effects smooth the transition and make it difficult to predict the critical point of…

Disordered Systems and Neural Networks · Physics 2026-02-11 A. V. Goltsev , S. N. Dorogovtsev

Here we study the emergence of spontaneous leadership in large populations. In standard models of opinion dynamics, herding behavior is only obeyed at the local scale due to the interaction of single agents with their neighbors; while at…

Physics and Society · Physics 2015-06-11 Guillem Mosquera-Donate , Marian Boguna

Evolutionary game theory has proven to be an elegant framework providing many fruitful insights in population dynamics and human behaviour. Here, we focus on the aspect of behavioural plasticity and its effect on the evolution of…

Populations and Evolution · Quantitative Biology 2020-09-29 M. Kleshnina , K. Kaveh , K. Chatterjee

Wealthy individuals may be less tempted to defect than those with comparatively low payoffs. To take this into consideration, we introduce coevolutionary success-driven multigames in structured populations. While the core game is always the…

Physics and Society · Physics 2014-10-17 Attila Szolnoki , Matjaz Perc

Ideas, behaviors, and opinions spread through social networks. If the probability of spreading to a new individual is a non-linear function of the fraction of the individuals' affected neighbors, such a spreading process becomes a "complex…

Physics and Society · Physics 2023-08-30 Julian Kates-Harbeck , Michael M. Desai

Based on the adiabatic theory for the evolutionary minority game (EMG) that we proposed earlier[1], we perform a detail analysis of the EMG limited to three groups of agents. We derive a formula for the critical point of the transition from…

Statistical Mechanics · Physics 2009-11-10 Kan Chen , Bing-Hong Wang , Baosheng Yuan

In this paper, we introduce a framework to study local interactions due to the presence of herding behavior in a minority game. The idea behind this approach is to consider that some of the agents who play the game believe that some of…

Computational Physics · Physics 2007-05-23 Daniel Oliveira Cajueiro , Reinaldo Soares De Camargo

We consider the effect of network structure on the evolution of a population. Models of this kind typically consider a population of fixed size and distribution. Here we consider eco-evolutionary dynamics where population size and…

Populations and Evolution · Quantitative Biology 2023-04-05 Karan Pattni , Wajid Ali , Mark Broom , Kieran J Sharkey

People are often divided into conformists and contrarians, the former tending to align to the majority opinion in their neighborhood and the latter tending to disagree with that majority. In practice, however, the contrarian tendency is…

Cellular Automata and Lattice Gases · Physics 2013-12-16 Franco Bagnoli , Raul Rechtman

Meta-population networks are effective tools for capturing population movement across distinct regions, but the assumption of well-mixed regions fails to capture the reality of population higher-order interactions. As a multidimensional…

Physics and Society · Physics 2024-06-18 Yanyi Nie , Yanbing Liu , Qixuan Cao , Tao Lin , Wei Wang

Information diffusion on social networks has been described as a collective outcome of threshold behaviors in the framework of threshold models. However, since the existing models do not take into account individuals' optimization problem,…

Physics and Society · Physics 2022-09-08 Teruyoshi Kobayashi

Human diseases spread over networks of contacts between individuals and a substantial body of recent research has focused on the dynamics of the spreading process. Here we examine a model of two competing diseases spreading over the same…

Physics and Society · Physics 2015-03-19 Brian Karrer , M. E. J. Newman

We study the following game on a finite graph $G = (V, E)$. At the start, each edge is assigned an integer $n_e \ge 0$, $n = \sum_{e \in E} n_e$. In round $t$, $1 \le t \le n$, a uniformly random vertex $v \in V$ is chosen and one of the…

Probability · Mathematics 2016-09-21 Antal A. Járai

Synchronization, cooperation, and chaos are ubiquitous phenomena in nature. In a population composed of many distinct groups of individuals playing the prisoner's dilemma game, there exists a migration dilemma: No cooperator would migrate…

Populations and Evolution · Quantitative Biology 2021-02-22 Shubhadeep Sadhukhan , Rohitashwa Chattopadhyay , Sagar Chakraborty

The notion of concept drift refers to the phenomenon that the distribution, which is underlying the observed data, changes over time; as a consequence machine learning models may become inaccurate and need adjustment. While there do exist…

Machine Learning · Computer Science 2020-06-24 Fabian Hinder , Barbara Hammer

Despite its remarkable empirical success as a highly competitive branch of artificial intelligence, deep learning is often blamed for its widely known low interpretation and lack of firm and rigorous mathematical foundation. However, most…

Machine Learning · Computer Science 2018-10-04 Wendi Xu , Ming Zhang