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In this paper, we examine the long-run behavior of regularized, no-regret learning in finite games. A well-known result in the field states that the empirical frequencies of no-regret play converge to the game's set of coarse correlated…

Computer Science and Game Theory · Computer Science 2023-11-07 Victor Boone , Panayotis Mertikopoulos

Spatial structure can play an important role in the evolution of cooperative behavior and the achievement of collective success of a population. In this paper, we explore the role of random and directed motion on spatial pattern formation…

Populations and Evolution · Quantitative Biology 2025-09-26 Tianyong Yao , Chenning Xu , Daniel B. Cooney

Evolutionary prisoner's dilemma games are studied with players located on square lattice and random regular graphs defining four neighbors for each one. The players follow one of the three strategies: tit-for-tat, unconditional cooperation,…

Physics and Society · Physics 2009-11-13 Attila Szolnoki , Matjaz Perc , Gyorgy Szabo

Unambiguous identification of the rewards driving behaviours of entities operating in complex open-ended real-world environments is difficult, partly because goals and associated behaviours emerge endogenously and are dynamically updated as…

Machine Learning · Computer Science 2024-05-03 Richard M. Bailey

Involution, a phenomenon of excessive competition with diminishing returns, has become a pressing socio-economic concern in contemporary China, prompting both academic inquiry and policy interventions. This paper proposes an evolutionary…

Physics and Society · Physics 2026-03-16 Bo Li , Qiwen Ge , Yong Shi

This paper considers an opportunistic scheduling problem over a renewal system. A controller observes a random event at the beginning of each renewal frame and then chooses an action in response to the event, which affects the duration of…

Optimization and Control · Mathematics 2019-06-10 Xiaohan Wei , Michael J. Neely

In real-life complex systems, individuals often encounter multiple social dilemmas that cannot be effectively captured using a single-game model. Furthermore, the environment and limited resources both play a crucial role in shaping…

Physics and Society · Physics 2025-04-15 Chengbin Sun , Alfonso de Miguel-Arribas , Chaoqian Wang , Haoxiang Xia , Yamir Moreno

We present a general framework for evolutionary learning to emergent unbiased state representation without any supervision. Evolutionary frameworks such as self-play converge to bad local optima in case of multi-agent reinforcement learning…

Machine Learning · Statistics 2023-02-03 Shohei Ohsawa

Robots that are trained to perform a task in a fixed environment often fail when facing unexpected changes to the environment due to a lack of exploration. We propose a principled way to adapt the policy for better exploration in changing…

Robotics · Computer Science 2019-05-10 Xingyu Lin , Pengsheng Guo , Carlos Florensa , David Held

Automated decision-making tools increasingly assess individuals to determine if they qualify for high-stakes opportunities. A recent line of research investigates how strategic agents may respond to such scoring tools to receive favorable…

Machine Learning · Computer Science 2021-10-28 Keegan Harris , Hoda Heidari , Zhiwei Steven Wu

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 investigate the impact of payoff shocks on the evolution of large populations of myopic players that employ simple strategy revision protocols such as the "imitation of success". In the noiseless case, this process is governed by the…

Probability · Mathematics 2014-12-30 Panayotis Mertikopoulos , Yannick Viossat

We study a coevolutionary public goods game on a dynamic hypergraph, where an individual's payoff directly determines the number of hyperedges it can join. In the proposed mechanism, nodes adjust their participation according to the group…

Physics and Society · Physics 2026-05-27 Yichao Yao , Yuji Zhang , Juan Wu , Minyu Feng , Attila Szolnoki

In the evolutionary minority game, agents are allowed to evolve their strategies (``mutate'') based on past experience. We explore the dependence of the system's global behavior on the response time and the mutation threshold of the agents.…

Statistical Mechanics · Physics 2009-11-10 Shahar Hod , Ehud Nakar

Feedback-evolving games is a framework that models the co-evolution between payoff functions and an environmental state. It serves as a useful tool to analyze many social dilemmas such as natural resource consumption, behaviors in…

Computer Science and Game Theory · Computer Science 2024-08-23 Keith Paarporn , James Nelson

Interactions among individuals in natural populations often occur in a dynamically changing environment. Understanding the role of environmental variation in population dynamics has long been a central topic in theoretical ecology and…

Populations and Evolution · Quantitative Biology 2021-05-18 Feng Huang , Ming Cao , Long Wang

We consider a stochastic model for evolution of group-structured populations in which interactions between group members correspond to the Prisoner's Dilemma or the Hawk-Dove game. Selection operates at two organization levels: individuals…

Populations and Evolution · Quantitative Biology 2019-04-12 Daniel B. Cooney

Humans and other animals can adapt their social behavior in response to environmental cues including the feedback obtained through experience. Nevertheless, the effects of the experience-based learning of players in evolution and…

Populations and Evolution · Quantitative Biology 2011-04-05 Naoki Masuda , Mitsuhiro Nakamura

When users can benefit from certain predictive outcomes, they may be prone to act to achieve those outcome, e.g., by strategically modifying their features. The goal in strategic classification is therefore to train predictive models that…

Machine Learning · Computer Science 2023-06-12 Guy Horowitz , Nir Rosenfeld

In this work, we consider a population composed of a continuum of agents that seek to maximize a payoff function by moving on a network. The nodes in the network may represent physical locations or abstract choices. The population is…

Optimization and Control · Mathematics 2020-12-24 Nirabhra Mandal , Pavankumar Tallapragada
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