scholarly journals The limits of weak selection and large population size in evolutionary game theory

2017 ◽  
Vol 75 (5) ◽  
pp. 1285-1317 ◽  
Author(s):  
Christine Sample ◽  
Benjamin Allen
Author(s):  
Katia Sycara ◽  
Paul Scerri ◽  
Anton Chechetka

In this chapter, we explore the use of evolutionary game theory (EGT) (Weibull, 1995; Taylor & Jonker, 1978; Nowak & May, 1993) to model the dynamics of adaptive opponent strategies for large population of players. In particular, we explore effects of information propagation through social networks in Evolutionary Games. The key underlying phenomenon that the information diffusion aims to capture is that reasoning about the experiences of acquaintances can dramatically impact the dynamics of a society. We present experimental results from agent-based simulations that show the impact of diffusion through social networks on the player strategies of an evolutionary game and the sensitivity of the dynamics to features of the social network.


Author(s):  
Katia Sycara ◽  
Paul Scerri ◽  
Anton Chechetka

The chapter explores the use of evolutionary game theory (EGT) to model the dynamics of adaptive opponent strategies for a large population of players. In particular, it explores effects of information propagation through social networks in evolutionary games. The key underlying phenomenon that the information diffusion aims to capture is that reasoning about the experiences of acquaintances can dramatically impact the dynamics of a society. The chapter presents experimental results from agent-based simulations that show the impact of diffusion through social networks on the player strategies of an evolutionary game and the sensitivity of the dynamics to features of the social network.


Author(s):  
Katia Sycara ◽  
Paul Scerri ◽  
Anton Chechetka

In this chapter, we explore the use of evolutionary game theory (EGT) (Nowak & May, 1993; Taylor & Jonker, 1978; Weibull, 1995) to model the dynamics of adaptive opponent strategies for a large population of players. In particular, we explore effects of information propagation through social networks in evolutionary games. The key underlying phenomenon that the information diffusion aims to capture is that reasoning about the experiences of acquaintances can dramatically impact the dynamics of a society. We present experimental results from agent-based simulations that show the impact of diffusion through social networks on the player strategies of an evolutionary game and the sensitivity of the dynamics to features of the social network.


Author(s):  
Katia Sycara ◽  
Paul Scerri ◽  
Anton Chechetka

In this chapter, we explore the use of evolutionary game theory (EGT) (Nowak & May, 1993; Taylor & Jonker, 1978; Weibull, 1995) to model the dynamics of adaptive opponent strategies for a large population of pl ion propagation through social networks in evolutionary games. The key underlying phenomenon that the information diffusion aims to capture is that reasoning about the experiences of acquaintances can dramatically impact the dynamics of a society. We present experimental results from agent-based simulations that show the impact of diffusion through social networks on the player strategies of an evolutionary game and the sensitivity of the dynamics to features of the social network.


2003 ◽  
Vol 3 (1) ◽  
Author(s):  
In Ho Lee ◽  
Adam Szeidl ◽  
Akos Valentinyi

Early results of evolutionary game theory showed that the risk dominant equilibrium is uniquely selected in the long run under the best-response dynamics with mutation. Bergin and Lipman (1996) qualified this result by showing that for a given population size, the evolutionary process can select any strict Nash equilibrium if the probability of choosing a nonbest response is state-dependent. This paper shows that the unique selection of the risk dominant equilibrium is robust with respect to state dependent mutation in local interaction games. More precisely, for any given mutation structure there exists a minimum population size beyond which the risk dominant equilibrium is uniquely selected. Our result is driven by contagion and cohesion among players, which exist only in local interaction settings and favor the risk dominant strategy. Our result strengthens the equilibrium selection result of evolutionary game theory.


2014 ◽  
Vol 8 (1) ◽  
pp. 15-19
Author(s):  
Andrea Karcagi-Kovács

In recent years, game theory is more often applied to analyse several sustainable development issues such as climate change and biological diversity, but the explanations generally remain within a non-cooperative setting. In this paper, after reviewing important studies in this field, I will show that these methods and the assumptions upon which these explanations rest lack both descriptive accuracy and analytical power. I also argue that the problem may be better investigated within a framework of the evolutionary game theory that focuses more on the dynamics of strategy change influenced by the effect of the frequency of various competing strategies. Building on this approach, the paper demonstrates that evolutionary games can better reflect the complexity of sustainable development issues. It presents models of human – nature and human – human conflicts represented by two-player and multi-player games (with a very large population of competitors). The benefit in these games played several times (continuously) will be the ability of the human race to survive. Finally, the paper attempts to identify and classify the main problems of sustainable development on which the game theory could be applied and demonstrates that this powerful analytical tool has many further possibilities for analysing global ecological issues.


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