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A two-dimensional small-world type network, subject to spatial prisoners' dilemma dynamics and containing an influential node defined as a special node with a finite density of directed random links to the other nodes in the network, is…

Disordered Systems and Neural Networks · Physics 2009-11-07 Beom Jun Kim , Ala Trusina , Petter Holme , Petter Minnhagen , Jean S. Chung , M. Y. Choi

The emerging social network platforms enable users to share their own opinions, as well as to exchange opinions with others. However, adversarial network perturbation, where malicious users intentionally spread their extreme opinions,…

Computers and Society · Computer Science 2023-04-26 Yuejiang Li , Zhanjiang Chen , H. Vicky Zhao

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

We investigate two paradigms for studying the evolution of cooperation--Prisoner's Dilemma and Snowdrift game in an online friendship network obtained from a social networking site. We demonstrate that such social network has small-world…

Physics and Society · Physics 2009-11-13 Feng Fu , Xiaojie Chen , Lianghuan Liu , Long Wang

Complex networks are a great tool for simulating the outcomes of different strategies used within the iterated prisoners' dilemma game. However, because the strategies themselves rely on the connection between nodes, then initial network…

Physics and Society · Physics 2022-08-30 Louis Zhao , Chen Ye Gan , Minglu Zhao

Combined prosocial incentives, integrating reward for cooperators and punishment for defectors, are effective tools to promote cooperation among competing agents in population games. Existing research concentrated on how to adjust reward or…

Optimization and Control · Mathematics 2023-12-06 Shengxian Wang , Ming Cao , Xiaojie Chen

Artificial neural networks in general and deep learning networks in particular established themselves as popular and powerful machine learning algorithms. While the often tremendous sizes of these networks are beneficial when solving…

Machine Learning · Computer Science 2020-05-28 Moritz Seiler , Heike Trautmann , Pascal Kerschke

The significance of network structures in promoting group cooperation within social dilemmas has been widely recognized. Prior studies attribute this facilitation to the assortment of strategies driven by spatial interactions. Although…

Multiagent Systems · Computer Science 2024-08-20 Tianyu Ren , Xiao-Jun Zeng

In a social dilemma situation, where individual and collective interests are in conflict, it sounds a reasonable assumption that the presence of super or smart players, who simultaneously punish defection and reward cooperation without…

Physics and Society · Physics 2024-06-03 Hsuan-Wei Lee , Colin Cleveland , Attila Szolnoki

The iterated prisoner's dilemma is a game that produces many counter-intuitive and complex behaviors in a social environment, based on very simple basic rules. It illustrates that cooperation can be a good thing even in a competitive world,…

Computer Science and Game Theory · Computer Science 2020-09-07 Robert Prentner

We study the cooperation problem in the framework of evolutionary game theory using the prisoner's dilemma as metaphor of the problem. Considering the growing process of the system and individuals with imitation capacity, we show conditions…

Computer Science and Game Theory · Computer Science 2015-06-11 Ignacio Gomez Portillo

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

Various theoretical and empirical studies have accounted for why humans cooperate in competitive environments. Although prior work has revealed that network structure and multiplex interactions can promote cooperation, most theory assumes…

Physics and Society · Physics 2026-01-05 Jnanajyoti Bhaumik , Naoki Masuda

As neural networks become the tool of choice to solve an increasing variety of problems in our society, adversarial attacks become critical. The possibility of generating data instances deliberately designed to fool a network's analysis can…

Machine Learning · Computer Science 2021-03-19 Gabriel D. Cantareira , Rodrigo F. Mello , Fernando V. Paulovich

Securing dynamic networks against adversarial actions is challenging because of the need to anticipate and counter strategic disruptions by adversarial entities within complex network structures. Traditional game-theoretic models, while…

Computational Complexity · Computer Science 2023-12-21 Dhananjay Raju , Georgios Bakirtzis , Ufuk Topcu

Evolution of cooperation in the prisoner's dilemma game is studied where initially all players are linked via a regular graph, having four neighbors each. Simultaneously with the strategy evolution, players are allowed to make new…

Physics and Society · Physics 2009-03-27 Attila Szolnoki , Matjaz Perc , Zsuzsa Danku

We study the evolution of cooperation in structured populations within popular models of social dilemmas, whereby simple coevolutionary rules are introduced that may enhance players abilities to enforce their strategy on the opponent.…

Physics and Society · Physics 2009-02-16 Attila Szolnoki , Matjaz Perc

Social dilemmas are situations where individuals face a temptation to increase their payoffs at a cost to total welfare. Building artificially intelligent agents that achieve good outcomes in these situations is important because many real…

Artificial Intelligence · Computer Science 2018-03-05 Adam Lerer , Alexander Peysakhovich

A growing body of empirical evidence indicates that social and cooperative behavior can be affected by cognitive and neurological factors, suggesting the existence of state-based decision-making mechanisms that may have emerged by…

Populations and Evolution · Quantitative Biology 2017-08-23 Zoran Utkovski , Viktor Stojkoski , Lasko Basnarkov , Ljupco Kocarev

Deep neural networks are at the forefront of machine learning research. However, despite achieving impressive performance on complex tasks, they can be very sensitive: Small perturbations of inputs can be sufficient to induce incorrect…

Computer Vision and Pattern Recognition · Computer Science 2020-09-04 Alex Serban , Erik Poll , Joost Visser