scholarly journals The social evolution of genocide across time and geographic space: Perspectives from evolutionary game theory

Author(s):  
Charles H. Anderton

A standard evolutionary game theory model is used to reveal the interpersonal and geographic characteristics of a population that make it vulnerable to accepting the genocidal aims of political leaders. Under conditions identified in the space-less version of the model, genocide architects can engineer the social metamorphosis of a peaceful people-group into one that supports, or does not resist, the architects’ atrocity goals. The model reveals policy interventions that prevent the social evolution of genocide among the population. The model is then extended into geographic space by analyzing interactions among peaceful and aggressive phenotypes in a Moore neighborhood. Key concepts of the analyses are applied to the onset and spread of genocide during the Holocaust (1938-1945) and to the prevention of genocide in Côte d'Ivoire (2011). [JEL codes: C73, D74]

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.


2014 ◽  
Author(s):  
Jeremy Van Cleve

The evolution of social traits remains one of the most fascinating and feisty topics in evolutionary biology even after half a century of theoretical research. W. D. Hamilton shaped much of the field initially with his 1964 papers that laid out the foundation for understanding the effect of genetic relatedness on the evolution of social behavior. Early theoretical investigations revealed two critical assumptions required for Hamilton's rule to hold in dynamical models: weak selection and additive genetic interactions. However, only recently have analytical approaches from population genetics and evolutionary game theory developed sufficiently so that social evolution can be studied under the joint action of selection, mutation, and genetic drift. We review how these approaches suggest two timescales for evolution under weak mutation: (i) a short-term timescale where evolution occurs between a finite set of alleles, and (ii) a long-term timescale where a continuum of alleles are possible and populations evolve continuously from one monomorphic trait to another. We show how Hamilton's rule emerges from the short-term analysis under additivity and how non-additive genetic interactions can be accounted for more generally. This short-term approach reproduces, synthesizes, and generalizes many previous results including the one-third law from evolutionary game theory and risk dominance from economic game theory. Using the long-term approach, we illustrate how trait evolution can be described with a diffusion equation that is a stochastic analogue of the canonical equation of adaptive dynamics. Peaks in the stationary distribution of the diffusion capture classic notions of convergence stability from evolutionary game theory and generally depend on the additive genetic interactions inherent in Hamilton's rule. Surprisingly, the peaks of the long-term stationary distribution can predict the effects of simple kinds of non-additive interactions. Additionally, the peaks capture both weak and strong effects of social payoffs in a manner difficult to replicate with the short-term approach. Together, the results from the short and long-term approaches suggest both how Hamilton's insight may be robust in unexpected ways and how current analytical approaches can expand our understanding of social evolution far beyond Hamilton's original work.


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.


2019 ◽  
Vol 116 (27) ◽  
pp. 13276-13281 ◽  
Author(s):  
Joung-Hun Lee ◽  
Yoh Iwasa ◽  
Ulf Dieckmann ◽  
Karl Sigmund

Cooperation can be sustained by institutions that punish free-riders. Such institutions, however, tend to be subverted by corruption if they are not closely watched. Monitoring can uphold the enforcement of binding agreements ensuring cooperation, but this usually comes at a price. The temptation to skip monitoring and take the institution’s integrity for granted leads to outbreaks of corruption and the breakdown of cooperation. We model the corresponding mechanism by means of evolutionary game theory, using analytical methods and numerical simulations, and find that it leads to sustained or damped oscillations. The results confirm the view that corruption is endemic and transparency a major factor in reducing it.


2011 ◽  
Vol 71-78 ◽  
pp. 2085-2088
Author(s):  
Chun Chu ◽  
De Shan Tang

Analyze the opportunistic behavior between China and Japan in energy security cooperation with game theory. There are two types countries in the process of the cooperation, they are opportunistic and cooperating countries. To use of evolutionary game theory model of cooperation and energy cooperation between China and Japan in the opportunistic behavior analysis, the results show that under certain conditions, cooperation can be avoided the incidence of opportunistic behavior, if not satisfy the relevant constraints, the co-operation will inevitably.


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