scholarly journals Social evolution and genetic interactions in the short and long term

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):  
Yan Liu ◽  
Chenyao Lv ◽  
Hong Xian Li ◽  
Yan Li ◽  
Zhen Lei ◽  
...  

Managing quality risks of prefabricated components is one of the challenges for prefabricated construction. The Quality Liability Insurance for Prefabricated Components (QLIPC) is an effective approach to transfer such risks; however, limited research has been conducted regarding the development of QLIPC. This study introduces an Evolutionary Game Theory (EGT)-based approach incorporating decisions from both the government and insurance companies. In the EGT model, a payoff matrix under disparate strategies is constructed, and the evolutionary stable strategies (ESS) are deduced. The simulation calculation is then carried out by MATLAB using sample virtual data to demonstrate the analysis. The results show that the government should act as the game promoter because the QLIPC can reduce governance cost and has significant social benefits. This research contributes a theoretical framework to analyze the QLIPC development using the EGT theory, and it could help the government to make long-term strategies for developing the QLIPC market.


2021 ◽  
Author(s):  
Yuxun Zhou ◽  
Rahman Mohammad Mafizur ◽  
Khanam Rasheda ◽  
Brad R. Taylor

Abstract Purpose – Based on the fact that punishment and subsidy mechanisms affect the anti-epidemic incentives of major participants in a society, the issue of this paper is how the penalty and subsidy mechanisms affect the decisions of governments, businesses, and consumers during Corona Virus Disease 2019. The goal of this paper is to understand strategic selections from governments, enterprises, and consumers to maximize their respective utility during Corona Virus Disease 2019, and the impact of penalty and subsidy mechanism on the decisions of governments, businesses, and consumers.Design/Methodology/approach - This paper proposes a tripartite evolutionary game theory, involving governments, businesses, and consumers, to firstly analyze the evolutionary stable strategies and to secondly analyze the impact of penalty and subsidy mechanism on their strategy selection during Corona Virus Disease 2019. Thirdly, this paper uses numerical analysis to simulate the strategy formation process of governments, enterprises, and consumers in Japan and India based on their different penalty and subsidy mechanism.Findings – This paper suggests that there are four evolutionarily stable strategies corresponding to the actual anti-epidemic situations of different countries in reality. We find that different subsidy and penalty mechanisms lead to different evolutionary stable strategies. If governments, enterprises, and consumers fighting the pandemic together, the government need to set a low subsidy mechanism and a high penalty mechanism.Originality/value - There are some limitations in the literature, such as long term strategies, rational hypothesis, and convergence path analysis in higher dimensional evolutionary game theory. This paper fills the gap and extends the theory of COVID-19 management theory. Firstly, this paper has important practical significance. This paper finds out the long-term equilibrium strategies of governments, businesses, and consumers under Corona Virus Disease 2019, which can provide an important theoretical and decision-making basis for pandemic prevention and control. Secondly, our paper extends the analytical paradigm of the tripartite evolutionary game theory. We extend the analysis of the dynamic process from the initial point to the convergence point and make a theoretical contribution to the development of high-dimensional evolutionary game theory.


2020 ◽  
Vol 103 (sp1) ◽  
pp. 117
Author(s):  
Liling Lin ◽  
Chaorong Huang ◽  
Linfeng Zhao

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.


2021 ◽  
Author(s):  
Joel W McGlothlin ◽  
Erol Akcay ◽  
Edmund D Brodie ◽  
Allen J Moore ◽  
Jeremy Van Cleve

Two popular approaches for modeling social evolution, evolutionary game theory and quantitative genetics, ask complementary questions but are rarely integrated. Game theory focuses on evolutionary outcomes, with models solving for evolutionarily stable equilibria, whereas quantitative genetics provides insight into evolutionary processes, with models predicting short-term responses to selection. Here we draw parallels between evolutionary game theory and interacting phenotypes theory, which is a quantitative genetic framework for understanding social evolution. First, we show how any evolutionary game may be translated into two quantitative genetic selection gradients, nonsocial and social selection, which may be used to predict evolutionary change from a single round of the game. We show that synergistic fitness effects may alter predicted selection gradients, causing changes in magnitude and sign as the population mean evolves. Second, we show how evolutionary games involving plastic behavioral responses to partners can be modeled using indirect genetic effects, which describe how trait expression changes in response to genes in the social environment. We demonstrate that repeated social interactions in models of reciprocity generate indirect effects and conversely, that estimates of parameters from indirect genetic effect models may be used to predict the evolution of reciprocity. We argue that a pluralistic view incorporating both theoretical approaches will benefit empiricists and theorists studying social evolution. We advocate the measurement of social selection and indirect genetic effects in natural populations to test the predictions from game theory, and in turn, the use of game theory models to aid in the interpretation of quantitative genetic estimates.


Author(s):  
Cristina Bicchieri ◽  
Giacomo Sillari

Game theory aims to understand situations in which decision-makers interact strategically. Chess is an example, as are firms competing for business, politicians competing for votes, animals fighting over prey, bidders competing in auctions, threats and punishments in long-term relationships, and so on. In such situations, the outcome depends on what the parties do jointly. Decision-makers may be people, organizations, animals, or even genes. In this chapter, the authors review fundamental notions of game theory and their application to philosophy of science. In particular, Section 1 looks at games of complete information through normal and extensive form representations, introduce the notion of Nash equilibrium and its refinements. Section 2 touches on epistemic foundations and correlated equilibrium, and Section 3 examines repeated games and their importance for the analysis of altruism and cooperation. Section 4 deals with 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):  
Cristina Acedo ◽  
Antoni Gomila

RESUMENEn esta contribución pretendemos reivindicar la necesidad de tener en cuenta las relaciones de confianza a la hora de tratar de entender la evolución de la cooperación. En este artículo, tras motivar el interés de tener en cuenta el papel de la confianza en la evolución de la cooperación, revisamos el concepto de confianza, como una actitud compleja que presupone vinculación afectiva y expectativas normativas, y proponemos una tipología que permite ordenar su variedad. Sostenemos que la complejidad de la cooperación humana tiene que ver con la manera en que los homínidos desarrollaron el andamiaje psicológico que hizo posible la confianza, y tratamos de proponer un escenario de su origen.PALABRAS CLAVECONFIANZA, COOPERACIÓN, EVOLUCIÓN SOCIALABSTRACTIn this paper we contend that trust has to be taken into account to explain the evolution of human cooperation. After showing that current models within evolutionary game theory overlook the role of trust, we offer our understanding of this concept, as a complex attitude that involves affective filiations and normative expectations, and put forward a typology of kinds of trust. We argue that the complexity of human cooperation was made possible in the psychological scaffolding that characterizes hominid evolution and made trust relationships possible. We also advance an hypothesis about the origin of trust.KEYWORDSTRUST, COOPERATION, SOCIAL EVOLUTION


2014 ◽  
Author(s):  
Chaitanya S. Gokhale ◽  
Arne Traulsen

AbstractEvolutionary game theory has become one of the most diverse and far reaching theories in biology. Applications of this theory range from cell dynamics to social evolution. However, many applications make it clear that inherent non-linearities of natural systems need to be taken into account. One way of introducing such non-linearities into evolutionary games is by the inclusion of multiple players. An example is of social dilemmas, where group benefits could e.g. increase less than linear with the number of cooperators. Such multiplayer games can be introduced in all the fields where evolutionary game theory is already well established. However, the inclusion of non-linearities can help to advance the analysis of systems which are known to be complex, e.g. in the case of non-Mendelian inheritance. We review the diachronic theory and applications of multiplayer evolutionary games and present the current state of the field. Our aim is a summary of the theoretical results from well-mixed populations in infinite as well as finite populations. We also discuss examples from three fields where the theory has been successfully applied, ecology, social sciences and population genetics. In closing, we probe certain future directions which can be explored using the complexity of multiplayer games while preserving the promise of simplicity of evolutionary games.


Sign in / Sign up

Export Citation Format

Share Document