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Axelrod's model for the dissemination of culture combines two key ingredients of social dynamics: social influence, through which people become more similar when they interact, and homophily, which is the tendency of individuals to interact…

Physics and Society · Physics 2020-03-11 Sandro M. Reia , Paulo F. Gomes , José F. Fontanari

This article is concerned with the Axelrod model, a stochastic process which similarly to the voter model includes social influence, but unlike the voter model also accounts for homophily. Each vertex of the network of interactions is…

Probability · Mathematics 2012-05-08 Nicolas Lanchier

The Axelrod model is a spatial stochastic model for the dynamics of cultures that includes two key social mechanisms: homophily and social influence, respectively defined as the tendency of individuals to interact more frequently with…

Probability · Mathematics 2014-07-24 Nicolas Lanchier , Paul-Henri Moisson

We present an individual based model of cultural evolution, where interacting agents are coded by binary strings standing for strategies for action, blueprints for products or attitudes and beliefs. The model is patterned on an established…

Physics and Society · Physics 2016-08-16 Arwen E. Nicholson , Paolo Sibani

Axelrod's model for culture dissemination offers a nontrivial answer to the question of why there is cultural diversity given that people's beliefs have a tendency to become more similar to each other's as people interact repeatedly. The…

Physics and Society · Physics 2009-11-19 Lauro A. Barbosa , José F. Fontanari

We consider the model proposed by Axelrod for dissemination of cultures on a 2-dimensional squared lattice. We review this model from an analytic point of view. We define $\left\langle s(t)\right\rangle$ to quantify possible culture…

Physics and Society · Physics 2018-04-03 Nirina Maurice Hasina Tahiridimbisoa , Yabebal Tadesse

Shared opinions are an important feature in the formation of social groups. In this paper, we use the Axelrod model of cultural dissemination to represent opinion-based groups. In the Axelrod model, each agent has a set of features which…

The Axelrod model of cultural dissemination has been widely studied in the field of statistical mechanics. The traditional version of this agent-based model is to assign a cultural vector of $F$ components to each agent, where each…

Physics and Society · Physics 2021-12-23 Lucía Pedraza , Sebastián Pinto , Juan Pablo Pinasco , Pablo Balenzuela

Axelrod's model for the dissemination of culture contains two key factors required to model the process of diffusion of innovations, namely, social influence (i.e., individuals become more similar when they interact) and homophily (i.e.,…

Physics and Society · Physics 2015-12-09 Paulo F. C. Tilles , José F. Fontanari

The use of {\it dyadic interaction} between agents, in combination with {\it homophily} (the principle that ``likes attract'') in the Axelrod model for the study of cultural dissemination has two important problems: the prediction of…

Physics and Society · Physics 2015-05-18 Arezky H. Rodríguez , Y. Moreno

This work examines adaptive distributed learning strategies designed to operate under communication constraints. We consider a network of agents that must solve an online optimization problem from continual observation of streaming data.…

Machine Learning · Computer Science 2025-04-25 Marco Carpentiero , Vincenzo Matta , Ali H. Sayed

Adaptive social learning is a useful tool for studying distributed decision-making problems over graphs. This paper investigates the effect of combination policies on the performance of adaptive social learning strategies. Using…

Signal Processing · Electrical Eng. & Systems 2023-06-01 Ping Hu , Virginia Bordignon , Stefan Vlaski , Ali H. Sayed

We study the following communication variant of local search. There is some fixed, commonly known graph $G$. Alice holds $f_A$ and Bob holds $f_B$, both are functions that specify a value for each vertex. The goal is to find a local maximum…

Computer Science and Game Theory · Computer Science 2018-10-09 Yakov Babichenko , Shahar Dobzinski , Noam Nisan

We study distributed (strongly convex) optimization problems over a network of agents, with no centralized nodes. The loss functions of the agents are assumed to be \textit{similar}, due to statistical data similarity or otherwise. In order…

Optimization and Control · Mathematics 2022-04-12 Ye Tian , Gesualdo Scutari , Tianyu Cao , Alexander Gasnikov

We consider the following communication task in the multi-party setting, which involves a joint random variable $XYZMN$ with the property that $M$ is independent of $YZN$ conditioned on $X$ and $N$ is independent of $XZM$ conditioned on…

Information Theory · Computer Science 2020-03-24 Anurag Anshu , Penghui Yao

The design of distributed algorithms is central to the study of multiagent systems control. In this paper, we consider a class of combinatorial cost-minimization problems and propose a framework for designing distributed algorithms with a…

Systems and Control · Computer Science 2019-03-18 Rahul Chandan , Dario Paccagnan , Jason R. Marden

In this paper we consider a distributed coordination game played by a large number of agents with finite information sets, which characterizes emergence of a single dominant attribute out of a large number of competitors. Formally, $N$…

Economics · Quantitative Finance 2016-12-21 S. Agarwal , D. Ghosh , A. S. Chakrabarti

The Axelrod model is a spatial stochastic model for the dynamics of cultures which includes two important social factors: social influence, the tendency of individuals to become more similar when they interact, and homophily, the tendency…

Probability · Mathematics 2013-12-06 Nicolas Lanchier , Stylianos Scarlatos

In this work we derive the performance achievable by a network of distributed agents that solve, adaptively and in the presence of communication constraints, a regression problem. Agents employ the recently proposed ACTC…

Machine Learning · Computer Science 2025-04-25 Marco Carpentiero , Vincenzo Matta , Ali H. Sayed

Designing reward functions for efficiently guiding reinforcement learning (RL) agents toward specific behaviors is a complex task. This is challenging since it requires the identification of reward structures that are not sparse and that…

Machine Learning · Computer Science 2023-11-01 Dhawal Gupta , Yash Chandak , Scott M. Jordan , Philip S. Thomas , Bruno Castro da Silva
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