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This paper presents models and algorithms for interactive sensing in social networks where individuals act as sensors and the information exchange between individuals is exploited to optimize sensing. Social learning is used to model the…

Social and Information Networks · Computer Science 2013-12-31 Vikram Krishnamurthy , H. Vincent Poor

An evolving population, in which individual members (`agents') adapt their behaviour according to past experience, is of central importance to many disciplines. Because of their limited knowledge and capabilities, agents are forced to make…

Condensed Matter · Physics 2009-10-31 Neil F. Johnson , Pak Ming Hui , Rob Jonson , Ting Shek Lo

Fear is a critical brain function that enables us to learn to avoid danger via reinforcement learning (RL). While many researchers have argued that fear has evolved to escape predators, how varying predatory pressures have shaped fear and…

Populations and Evolution · Quantitative Biology 2026-02-10 Yuji Kanagawa , Kenji Doya

Cooperative behavior in real social dilemmas is often perceived as a phenomenon emerging from norms and punishment. To overcome this paradigm, we highlight the interplay between the influence of social networks on individuals, and the…

Physics and Society · Physics 2018-07-23 Dario Madeo , Chiara Mocenni

In this paper, we inspect well-known population genetics and social dynamics models. In these models, interacting individuals, while participating in a self-organizing process, give rise to the emergence of complex behaviors and patterns.…

Populations and Evolution · Quantitative Biology 2012-07-11 Sven Banisch , Tanya Araújo

This paper presents the results of computational experiments on the effects of social influence on individual and systemic behavior of situated cognitive agents in a product-consumer environment. Paired experiments were performed with…

Social and Information Networks · Computer Science 2012-04-17 Russell C. Thomas , John S. Gero

Machine learning has witnessed remarkable breakthroughs in recent years. As machine learning permeates various aspects of daily life, individuals and organizations increasingly interact with these systems, exhibiting a wide range of social…

Machine Learning · Computer Science 2024-08-06 Han Shao

We revisit a recently introduced agent model[ACS {\bf 11}, 99 (2008)], where economic growth is a consequence of education (human capital formation) and innovation, and investigate the influence of the agents' social network, both on an…

General Finance · Quantitative Finance 2009-11-13 Teresa Vaz Martins , Tanya Araujo , Maria Augusta Santos , Miguel St Aubyn

Understanding how the structure of community interactions is modified by coevolution is vital for understanding system responses to change at all scales. However, in absence of a group selection process, collective community behaviours…

Populations and Evolution · Quantitative Biology 2015-06-23 Daniel A. Power , Richard A. Watson , Eörs Szathmáry , Rob Mills , Simon T Powers , C Patrick Doncaster , Błażej Czapp

Many organisms live in populations structured by space and by class, exhibit plastic responses to their social partners, and are subject to non-additive ecological and fitness effects. Social evolution theory has long recognized that all of…

Populations and Evolution · Quantitative Biology 2014-04-24 Jeremy Van Cleve , Erol Akçay

People make strategic decisions many times a day - during negotiations, when coordinating actions with others, or when choosing partners for cooperation. The resulting dynamics can be studied with learning theory and evolutionary game…

Populations and Evolution · Quantitative Biology 2026-03-26 Marta C. Couto , Fernando P. Santos , Christian Hilbe

Collective, especially group-based, managerial decision making is crucial in organizations. Using an evolutionary theoretic approach to collective decision making, agent-based simulations were conducted to investigate how human collective…

Multiagent Systems · Computer Science 2019-02-20 Shelley D. Dionne , Hiroki Sayama , Francis J. Yammarino

Bias exists in how we pick leaders, who we perceive as being influential, and who we interact with, not only in society, but in organizational contexts. Drawing from leadership emergence and social influence theories, we investigate…

Multiagent Systems · Computer Science 2023-04-06 Andria L. Smith , Simon Heuschkel , Ksenia Keplinger , Charley M. Wu

The origin of altruistic behavior, i.e. the behavior that is useful for a population or a species but goes at the expense of an altruistic individual, has long been a challenge for students of evolutionary biology. The populations with…

Populations and Evolution · Quantitative Biology 2010-02-24 T. Kulich , J. Flegr

In decentralised autonomous systems it is the interactions between individual agents which govern the collective behaviours of the system. These local-level interactions are themselves often governed by an underlying network structure.…

Multiagent Systems · Computer Science 2023-06-07 Michael Crosscombe , Jonathan Lawry

Homophily, the tendency of individuals to associate with others who share similar traits, has been identified as a major driving force in the formation and evolution of social ties. In many cases, it is not clear if homophily is the result…

Physics and Society · Physics 2017-09-01 Ivan Smirnov , Stefan Thurner

Understanding why we age is a long-lived open problem in evolutionary biology. Aging is prejudicial to the individual and evolutionary forces should prevent it, but many species show signs of senescence as individuals age. Here, I will…

Populations and Evolution · Quantitative Biology 2012-01-24 André C. R. Martins

The origin of agriculture represents a major evolutionary transition and a paradigmatic example of how complex collective behaviors emerge from simple interactions. Here we introduce an artificial society of reinforcement learning agents…

Multiagent Systems · Computer Science 2026-05-26 Gautier Hamon , Martí Sánchez-Fibla , Clément Moulin-Frier , Ricard Solé

Interacting many-body physical systems ranging from neural networks in the brain to folding proteins to self-modifying electrical circuits can learn to perform diverse tasks. This learning, both in nature and in engineered systems, can…

Disordered Systems and Neural Networks · Physics 2024-02-22 Menachem Stern , Andrea J. Liu , Vijay Balasubramanian

We model recruitment in adaptive social networks in the presence of birth and death processes. Recruitment is characterized by nodes changing their status to that of the recruiting class as a result of contact with recruiting nodes. Only a…

Populations and Evolution · Quantitative Biology 2012-07-20 Maxim S. Shkarayev , Ira B. Schwartz , Leah B. Shaw
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