Abstract:Standard Evolutionary Game Theory framework is a useful tool to study large interacting systems and to understand the strategic behavior of individuals in such complex systems. Adding an individual state to model local feature of each player in this context, allows one to study a wider range of problems in various application areas as networking, biology, etc. In this paper, we introduce such an extension of evolutionary game framework and particularly, we focus on the dynamical aspects of this system. Precise… Show more
“…This line of research has been developing in a fast pace recently. In [ 6 ], the authors have proposed the state policy coupled dynamics model for extending the current evolutionary game by introducing independent state transitions of players. They have focused on the coupling of replicator dynamics and individual player’s Markov decision process.…”
Section: Related Workmentioning
confidence: 99%
“…The assumption that functions are continuously differentiable with respect to w and x implies that they are locally Lipschitz with respect to w and x . Combining the assumption of functions being Lipschitz, the existence of solutions to the coupled system ( 1 ) and ( 3 ) is guaranteed [ 6 ]. Fig.…”
The recent COVID-19 pandemic has led to an increasing interest in the modeling and analysis of infectious diseases. The pandemic has made a significant impact on the way we behave and interact in our daily life. The past year has witnessed a strong interplay between human behaviors and epidemic spreading. In this paper, we propose an evolutionary game-theoretic framework to study the coupled evolution of herd behaviors and epidemics. Our framework extends the classical degree-based mean-field epidemic model over complex networks by coupling it with the evolutionary game dynamics. The statistically equivalent individuals in a population choose their social activity intensities based on the fitness or the payoffs that depend on the state of the epidemics. Meanwhile, the spreading of the infectious disease over the complex network is reciprocally influenced by the players’ social activities. We analyze the coupled dynamics by studying the stationary properties of the epidemic for a given herd behavior and the structural properties of the game for a given epidemic process. The decisions of the herd turn out to be strategic substitutes. We formulate an equivalent finite-player game and an equivalent network to represent the interactions among the finite populations. We develop a structure-preserving approximation technique to study time-dependent properties of the joint evolution of the behavioral and epidemic dynamics. The resemblance between the simulated coupled dynamics and the real COVID-19 statistics in the numerical experiments indicates the predictive power of our framework.
“…This line of research has been developing in a fast pace recently. In [ 6 ], the authors have proposed the state policy coupled dynamics model for extending the current evolutionary game by introducing independent state transitions of players. They have focused on the coupling of replicator dynamics and individual player’s Markov decision process.…”
Section: Related Workmentioning
confidence: 99%
“…The assumption that functions are continuously differentiable with respect to w and x implies that they are locally Lipschitz with respect to w and x . Combining the assumption of functions being Lipschitz, the existence of solutions to the coupled system ( 1 ) and ( 3 ) is guaranteed [ 6 ]. Fig.…”
The recent COVID-19 pandemic has led to an increasing interest in the modeling and analysis of infectious diseases. The pandemic has made a significant impact on the way we behave and interact in our daily life. The past year has witnessed a strong interplay between human behaviors and epidemic spreading. In this paper, we propose an evolutionary game-theoretic framework to study the coupled evolution of herd behaviors and epidemics. Our framework extends the classical degree-based mean-field epidemic model over complex networks by coupling it with the evolutionary game dynamics. The statistically equivalent individuals in a population choose their social activity intensities based on the fitness or the payoffs that depend on the state of the epidemics. Meanwhile, the spreading of the infectious disease over the complex network is reciprocally influenced by the players’ social activities. We analyze the coupled dynamics by studying the stationary properties of the epidemic for a given herd behavior and the structural properties of the game for a given epidemic process. The decisions of the herd turn out to be strategic substitutes. We formulate an equivalent finite-player game and an equivalent network to represent the interactions among the finite populations. We develop a structure-preserving approximation technique to study time-dependent properties of the joint evolution of the behavioral and epidemic dynamics. The resemblance between the simulated coupled dynamics and the real COVID-19 statistics in the numerical experiments indicates the predictive power of our framework.
“…Vertexes 15, 16 and corresponding edges of the graph (see Figure 1) describe elements of the mechanisms of environmental and economic management [4][5][6][7][8][9]. The goal of the management is to change ecological and socio-economic parameters of equilibrium.…”
Section: The Subsystem Of Cognitive Analysismentioning
There is a computer decision support system (CDSS) for urbanization of the northern part of the Volga-Akhtuba floodplain. This system includes subsystems of cognitive and game-theoretic analysis, geoinformation and hydrodynamic simulations. The paper presents the cognitive graph, two-level and three-level models of hierarchical games for the cases of uncontrolled and controlled development of the problem situation. We described the quantitative analysis of the effects of different strategies for the spatial distribution of the urbanized territories. For this reason we conducted the territory zoning according to the level of negative consequences of urbanization for various agents. In addition, we found an analytical solution for games with the linear dependence of the average flooded area on the urbanized area. We numerically computed a game equilibrium for dependences derived from the imitational geoinformation and hydrodynamic modeling of flooding. As the result, we showed that the transition to the three-level management system and the implementation of an optimal urbanization strategy minimize its negative consequences.
“…This pioneering effort has centered around the works of Eitan Altman, and his colleagues Ilaria Brunetti and Yezekael Hayel [15][16][17][18][19][20], who introduce the Markov-Decision-Evolutionary-Game (MDEG) and variants thereof.…”
Abstract:A new evolutionary game is introduced which incorporates states and actions into the strategies of the organisms of the evolving populations. The game centrally features actions that result in demographic flow between states that may not conserve organism numbers. It is by this feature that the game encapsulate a range of other evolutionary games, and can encode almost very complex interactions between organisms, species and populations. The game's formalism is expounded and the nature of the game's equilibrium is discussed. This discussion leads to an algorithm for numerically determining the stable equilibrium points which is exemplified in the context of a modified Hawk-Dove game. The game's flexibility for modeling population dynamics is evaluated and compared with other evolutionary games.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
