Evolutionary Dynamics of Biological Games

By Martin A. Nowak, Karl Sigmund. Science, 2004

1,136 citations recorded by the source corpus.

Subfields: Genetics, Public Health, Environmental and Occupational Health, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/2feedd23395f882e40dc46f864f2a536c0fe0234

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Citations in the corpus

Evolutionary game dynamics (2011, background): “The dynamic describes how the strategy distribution in a large population of players changes over time, due to selection, imitation or other kinds of adaptation [4,5,7,8].”
Imitation dynamics of vaccination behaviour on social networks (2011, methodology): “Motivated by the above considerations, we propose a simple agent-based model in the spirit of evolutionary game dynamics (Maynard-Smith 1982, Nowak & Sigmund 2004, Nowak 2006a) to study the voluntary vaccination dilemma.”
The behavioural ecology of personality: consistent individual differences from an adaptive perspective (2004, background): “The conditions favouring the evolution of one or other of these forms of mixed evolutionarily stable strategies have yet to be elucidated in general, although investigating the evolutionary dynamics of biological games ( Nowak & Sigmund 2004 ) may generate insights.”
The Developmental, Physiological, Neural, and Genetical Causes and Consequences of Frequency-Dependent Selection in the Wild (2006, background): “Fitness gains of replicators, copies of single alleles, often come at the expense of the fitness of individual phenotypes in which replicators reside (Nowak & Sigmund 2004).”
Evolutionary games on graphs (2006, background): “ not an ESS it is unstable against the attack of some superior mutants (not present originally in the population). Adaptive Dynamics (Metz et al., 1996; Dieckmann and Metz, 1996; Geritz et al., 1997; Nowak and Sigmund, 2004) models the situation when the mutation rate is low and possible mutants onl”
Evolution and impact of subclonal mutations in chronic lymphocytic leukemia (2013, positive): “This knowledge challenges us to develop therapeutic paradigms that not only target specific drivers (i.e., ‘‘targeted therapy’’) but also the evolutionary landscape (Nowak and Sigmund, 2004) of these drivers.”
Mathematical Modeling of Microbial Community Dynamics: A Methodological Review (2014, background): “This frequency-dependent selection concept implies that the fitness landscape is altered as the population structure and member abundance change with time [106].”
Games on graphs (2014, background): “Evolutionary game theory [54], [53], [17], [89], [118], [37], [38], [66], [12] is the study of evolution when selection depends on the relative abundance (D frequency) of strategies or phenotypes in the population.”