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Related papers: Network and timing effects in social learning

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We consider the effects of social learning on the individual learning and genetic evolution of a colony of artificial agents capable of genetic, individual and social modes of adaptation. We confirm that there is strong selection pressure…

Artificial Intelligence · Computer Science 2014-06-12 Chris Marriott , Jobran Chebib

The idea of a collective intelligence behind the complex natural structures built by organisms suggests that the organization of social networks is selected so as to optimize problem-solving competence at the group-level. Here we study the…

Social and Information Networks · Computer Science 2016-09-19 José F. Fontanari , Francisco A. Rodrigues

This work is aimed at studying realistic social control strategies for social networks based on the introduction of random information into the state of selected driver agents. Deliberately exposing selected agents to random information is…

Social and Information Networks · Computer Science 2018-07-23 Marco Cremonini , Francesca Casamassima

People often learn from other's actions when they make decisions while doing online shopping. This kind of observational learning may lead to information cascades, which means agents might ignore their own signals and follow the 'trend'…

Social and Information Networks · Computer Science 2024-02-08 Yuming Han

We study a social learning scheme where at every time instant, each agent chooses to receive information from one of its neighbors at random. We show that under this sparser communication scheme, the agents learn the truth eventually and…

Multiagent Systems · Computer Science 2022-05-13 Yunus Inan , Mert Kayaalp , Emre Telatar , Ali H. Sayed

When individuals in a social network learn about an unknown state from private signals and neighbors' actions, the network structure often causes information loss. We consider rational agents and Gaussian signals in the canonical sequential…

Theoretical Economics · Economics 2026-02-20 Krishna Dasaratha , Kevin He

We develop original models to study interacting agents in financial markets and in social networks. Within these models randomness is vital as a form of shock or news that decays with time. Agents learn from their observations and learning…

Mathematical Finance · Quantitative Finance 2023-07-14 Ionel Popescu , Tushar Vaidya

When does society eventually learn the truth, or take the correct action, via observational learning? In a general model of sequential learning over social networks, we identify a simple condition for learning dubbed excludability.…

Theoretical Economics · Economics 2024-04-05 Navin Kartik , SangMok Lee , Tianhao Liu , Daniel Rappoport

In recent years online social networks have become increasingly prominent in political campaigns and, concurrently, several countries have experienced shock election outcomes. This paper proposes a model that links these two phenomena. In…

Theoretical Economics · Economics 2020-11-03 Edoardo Gallo , Alastair Langtry

Many societies are organized in networks that are formed by people who meet and interact over time. In this paper, we present a first model to capture the micro-foundations of social networks evolution, where boundedly rational agents of…

Social and Information Networks · Computer Science 2015-08-17 Ahmed M. Alaa , Kartik Ahuja , Mihaela van der Schaar

Many socioeconomic phenomena, such as technology adoption, collaborative problem-solving, and content engagement, involve a collection of agents coordinating to take a common action, aligning their decisions to maximize their individual…

Physics and Society · Physics 2024-03-26 Yifei Zhang , Marcos M. Vasconcelos

When consequential decisions are informed by algorithmic input, individuals may feel compelled to alter their behavior in order to gain a system's approval. Models of agent responsiveness, termed "strategic manipulation," analyze the…

Machine Learning · Computer Science 2019-05-13 Lily Hu , Nicole Immorlica , Jennifer Wortman Vaughan

Despite the tremendous advancements in the field of network theory, very few studies have taken weights in the interactions into consideration that emerge naturally in all real world systems. Using random matrix analysis of a weighted…

Physics and Society · Physics 2016-02-25 Camellia Sarkar , Sarika Jalan

The process by which new ideas, innovations, and behaviors spread through a large social network can be thought of as a networked interaction game: Each agent obtains information from certain number of agents in his friendship neighborhood,…

Computer Science and Game Theory · Computer Science 2012-08-28 Javad Ghaderi , R. Srikant

A generic property of biological, social and economical networks is their ability to evolve in time, creating and suppressing interactions. We approach this issue within the framework of an adaptive network of agents playing a Prisoner's…

Adaptation and Self-Organizing Systems · Physics 2014-10-20 Martin G. Zimmermann , Victor M. Eguiluz , Maxi San Miguel

The role of perception in conscious behavior and decision-making is examined. The effect of spatial and temporal stochasticity in the acquisition of beliefs is discussed. The idea of an agent as a locally strongly coupled group of states…

Adaptation and Self-Organizing Systems · Physics 2009-01-27 Fariel Shafee

We study the self-assembly of a complex network of collaborations among self-interested agents. The agents can maintain different levels of cooperation with different partners. Further, they continuously, selectively, and independently…

Physics and Society · Physics 2015-05-13 Anne-Ly Do , Lars Rudolf , Thilo Gross

The orderly behaviors observed in large-scale groups, such as fish schooling and the organized movement of crowds, are both ubiquitous and essential for the survival and stability of these systems. Understanding how such complex collective…

Physics and Society · Physics 2025-10-28 Yu Xia , Alex McAvoy , Qi Su

While it has long been recognized that a team of individual learning agents can be greater than the sum of its parts, recent work has shown that larger teams are not necessarily more effective than smaller ones. In this paper, we study why…

Artificial Intelligence · Computer Science 2023-06-29 David Radke , Kate Larson , Tim Brecht , Kyle Tilbury

We consider model social networks in which information propagates directionally across layers of rational agents. Each agent makes a locally optimal estimate of the state of the world, and communicates this estimate to agents downstream.…

Methodology · Statistics 2017-09-22 Simon Stolarczyk , Manisha Bhardwaj , Kevin E. Bassler , Wei Ji Ma , Kresimir Josic