Evolutionary Games and Population Dynamics

By Josef Hofbauer, Karl Sigmund. 1998

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In Game & Decision Theory

Citations in the corpus

OpenSpiel: A Framework for Reinforcement Learning in Games (2019, methodology): “This is equivalent to updating the policy of a parameterized replicator dynamics from evolutionary game theory [27, 61] using an Euler discretization.”
Evolutionary Dynamics of Multi-Agent Learning: A Survey (2015, methodology): “the textbooks by Weibull (1997) and Hofbauer and Sigmund (1998) for an introduction.”
A new route to the evolution of cooperation (2006, background): “In well-mixed populations, in which each agent interacts with all other agents, evolution under replicator dynamics ( Hofbauer & Sigmund, 1998; Gintis, 2000) shows that cooperators are unable to resist invasion by defectors.”
Negotiation over offspring care—how should parents respond to each other's efforts? (2006, unknown): “To address this question, we make the assumption that evolutionary change is described by the continuous-time adaptive dynamics of Hofbauer and Sigmund (1998) .”
Neural methods for non-standard data (2004, methodology): “The Replicator dynamics is derived from evolutionary game theory [38].”
Coevolutionary games - A mini review (2009, unknown): “This unadorned scenario is actually realized in the well-mixed prisoner’s dilemma game, where defectors reign supreme (Hofbauer and Sigmund, 1998).”
Evolutionary Algorithms for Solving Multi-Objective Problems (2002, background): “6 Investigate "evolutionary game theory" (Smith, 1982; Hofbauer and Sigmund, 1998; Weibull, 1997) and discuss its potential applicability to multicriteria decision making using MOEAs.”
Imitation dynamics of vaccination behaviour on social networks (2011, background): “First-order approximation of the imita-136 tion dynamics closely approximates the replicator dynamics (Hofbauer & Sigmund 1998, Schuster & Sigmund 1983, Taylor & Jonker 1978), which in this game converge to the unique evolutionarily stable strategy–the Nash equilibrium (see ESM).”
Updates on mechanisms of maintenance of species diversity (2018, background): “A number of references detail these ideas and their application (Hofbauer & Sigmund, 1998; Jansen & Sigmund, 1998; Kang & Chesson, 2010).”
The semantic and pragmatic underpinnings of grammaticalization paths: The progressive to imperfective shift (2015, methodology): “…dynamics Evolutionary game dynamics have been used to describe and understand the behavior of large populations over time as an evolving game, and in particular, changes in the frequencies of different strategies in a population over time (Taylor & Jonker 1978, Hofbauer & Sigmund 1998).”
Macroeconomic impact of stranded fossil fuel assets (2018, background): “The diffusion patterns of technologies are functions of their own market share and those of others, which reproduces standard observed S-shaped diffusion profiles (a so-called evolutionary replicator dynamics equation, or Lotka-Volterra competition equation 53-55 ).”
Evolutionary Game Theory and Typology: A Case Study (2007, background): “19 See for instance Hofbauer and Sigmund (1998), pp.”
Evolutionary games on multilayer networks: a colloquium (2015, background): “Almost simultaneously with network science, in evolutionary game theory [8–11] leaps of progress have also been made, largely due to interdisciplinary approaches that link together knowledge from biology, sociology, economics as well as mathematics, physics and psychology [12–21].”