scholarly journals A Synthesis of Game Theory and Quantitative Genetic Models of Social Evolution

2021 ◽  
Author(s):  
Joel W McGlothlin ◽  
Erol Akcay ◽  
Edmund D Brodie ◽  
Allen J Moore ◽  
Jeremy Van Cleve
Keyword(s):  
Game Theory ◽  
Quantitative Genetics ◽  
Evolutionary Game Theory ◽  
Social Evolution ◽  
Evolutionary Game ◽  
Genetic Effects ◽  
Social Selection ◽  
Selection Gradients ◽  
Quantitative Genetic ◽  
Indirect Genetic Effects

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.

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

2014 ◽  
Author(s):  
Jeremy Van Cleve
Keyword(s):  
Game Theory ◽  
Evolutionary Game Theory ◽  
Social Evolution ◽  
Evolutionary Game ◽  
Genetic Interactions ◽  
Short Term ◽  
Hamilton’S Rule ◽  
Analytical Approaches ◽  
Hamilton's Rule

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.

scholarly journals Social evolution leads to persistent corruption

2019 ◽  
Vol 116 (27) ◽  
pp. 13276-13281 ◽  
Author(s):  
Joung-Hun Lee ◽  
Yoh Iwasa ◽  
Ulf Dieckmann ◽  
Karl Sigmund
Keyword(s):  
Game Theory ◽  
Numerical Simulations ◽  
Evolutionary Game Theory ◽  
Analytical Methods ◽  
Social Evolution ◽  
Evolutionary Game ◽  
Free Riders ◽  
Damped Oscillations

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.

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

2015 ◽  
Vol 10 (2) ◽  
Author(s):  
Charles H. Anderton
Keyword(s):  
Game Theory ◽  
Evolutionary Game Theory ◽  
Social Evolution ◽  
Evolutionary Game ◽  
Theory Model ◽  
Geographic Space ◽  
Policy Interventions ◽  
The Social ◽  
The Holocaust ◽  
Moore Neighborhood

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]

scholarly journals Confianza y cooperación. Una perspectiva evolutiva

2013 ◽  
Author(s):  
Cristina Acedo ◽  
Antoni Gomila
Keyword(s):  
Game Theory ◽  
Evolutionary Game Theory ◽  
Social Evolution ◽  
Evolutionary Game ◽  
Hominid Evolution ◽  
Trust Relationships ◽  
Normative Expectations

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

scholarly journals Evolutionary multiplayer games

2014 ◽  
Author(s):  
Chaitanya S. Gokhale ◽  
Arne Traulsen
Keyword(s):  
Game Theory ◽  
Evolutionary Game Theory ◽  
Social Evolution ◽  
Evolutionary Game ◽  
Evolutionary Games ◽  
Mendelian Inheritance ◽  
Multiplayer Games ◽  
Cell Dynamics ◽  
Natural Systems ◽  
Applied Ecology

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.

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