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In the natural world, life has found innumerable ways to survive and often thrive. Between and even within species, each individual is in some manner unique, and this diversity lends adaptability and robustness to life. In this work, we aim…

Machine Learning · Computer Science 2021-07-16 Kenneth Derek , Phillip Isola

We describe the dynamics of a simple adaptive network. The network architecture evolves to a number of disconnected components on which the dynamics is characterized by the possibility of differently synchronized nodes within the same…

Adaptation and Self-Organizing Systems · Physics 2015-05-28 V. Botella-Soler , P. Glendinning

The paper presents a model of two-speed evolution in which the payoffs in the population game (or, alternatively, the individual preferences) slowly adjust to changes in the aggregate behavior of the population. The model investigates how,…

Theoretical Economics · Economics 2021-06-16 George Loginov

The emergence of cooperation among self-interested agents has been a key concern of the multi-agent systems community for decades. With the increased importance of network-mediated interaction, researchers have shifted the attention on the…

Physics and Society · Physics 2022-02-09 Jacques Bara , Paolo Turrini , Giulia Andrighetto

We study repeated games where players use an exponential learning scheme in order to adapt to an ever-changing environment. If the game's payoffs are subject to random perturbations, this scheme leads to a new stochastic version of the…

Probability · Mathematics 2010-10-22 Panayotis Mertikopoulos , Aris L. Moustakas

The theory of learning in games has extensively studied situations where agents respond dynamically to each other by optimizing a fixed utility function. However, in real situations, the strategic environment varies as a result of past…

Computer Science and Game Theory · Computer Science 2022-07-15 Brandon C. Collins , Shouhuai Xu , Philip N. Brown

We show that strategy independent adaptations of random interaction networks can induce powerful mechanisms, ranging from the Red Queen to group selection, that promote cooperation in evolutionary social dilemmas. These two mechanisms…

Physics and Society · Physics 2009-10-13 Attila Szolnoki , Matjaz Perc

Evolution of distribution of strategies in game theory is an interesting question that has been studied only for specific cases. Here I develop a general method to extend analysis of the evolution of continuous strategy distributions given…

Populations and Evolution · Quantitative Biology 2020-03-16 Georgiy Karev

In this paper we examine the relationship between the flow of the replicator dynamic, the continuum limit of Multiplicative Weights Update, and a game's response graph. We settle an open problem establishing that under the replicator, sink…

Computer Science and Game Theory · Computer Science 2023-02-02 Oliver Biggar , Iman Shames

The game interactions among individuals in nature are often uncertain and dynamically evolving, significantly influencing the persistence of cooperation. However, it remains a formidable challenge to effectively characterize these dynamic…

Computer Science and Game Theory · Computer Science 2026-03-24 Bin Pi , Minyu Feng , Liang-Jian Deng , Xiaojie Chen , Attila Szolnoki

We explore the evolutionary dynamics of two games - the Prisoner's Dilemma and the Snowdrift Game - played within distinct networks (layers) of interdependent networks. In these networks imitation and interaction between individuals of…

Physics and Society · Physics 2014-04-10 M. D. Santos , S. N. Dorogovtsev , J. F. F. Mendes

Learning to cooperate with other agents is challenging when those agents also possess the ability to adapt to our own behavior. Practical and theoretical approaches to learning in cooperative settings typically assume that other agents'…

Computer Science and Game Theory · Computer Science 2022-11-29 Robert Loftin , Frans A. Oliehoek

We investigate a class of reinforcement learning dynamics where players adjust their strategies based on their actions' cumulative payoffs over time - specifically, by playing mixed strategies that maximize their expected cumulative payoff…

Optimization and Control · Mathematics 2016-02-10 Panayotis Mertikopoulos , William H. Sandholm

We study the evolution of behavior under reinforcement learning in a Prisoner's Dilemma where agents interact in a regular network and can learn about whether they play one-shot or repeatedly by incurring a cost of deliberation. With…

Physics and Society · Physics 2024-03-28 Rossana Mastrandrea , Leonardo Boncinelli , Ennio Bilancini

We present a model that takes into account the coupling between evolutionary game dynamics and social influence. Importantly, social influence and game dynamics take place in different domains, which we model as different layers of a…

Physics and Society · Physics 2017-02-22 Roberta Amato , Albert Díaz-Guilera , Kaj-Kolja Kleineberg

This paper investigates the long-term behavior of an interacting particle system of interest in the hot topic of evolutionary game theory. Each site of the $d$-dimensional integer lattice is occupied by a player who is characterized by one…

Probability · Mathematics 2016-06-07 Eric Foxall , Nicolas Lanchier

When a prediction algorithm serves a collection of users, disparities in prediction quality are likely to emerge. If users respond to accurate predictions by increasing engagement, inviting friends, or adopting trends, repeated learning…

Machine Learning · Computer Science 2025-11-27 Eden Saig , Nir Rosenfeld

Urban structures encompass settlements, characterized by the spatial distribution of built-up areas, but also transportation structures, to connect these built-up areas. These two structures are very different in their origin and function,…

Physics and Society · Physics 2016-06-20 Frank Schweitzer , Vahan Nanumyan

Learning from a partner who collects higher payoff is a frequently used working hypothesis in evolutionary game theory. One of the alternative dynamical rules is when the focal player prefers to follow the strategy choice of the majority in…

Physics and Society · Physics 2018-09-14 Attila Szolnoki , Xiaojie Chen

This paper extends the reinforcement learning ideas into the multi-agents system, which is far more complicated than the previously studied single-agent system. We studied two different multi-agents systems. One is the fully-connected…

Artificial Intelligence · Computer Science 2015-05-18 Zhipeng Wang , Mingbo Cai