Coevolutionary games - A mini review

By Matjaz Perc, Attila Szolnoki. Biosyst., 2009

1,806 citations recorded by the source corpus.

Prevalence of cooperation within groups of selfish individuals is puzzling in that it contradicts with the basic premise of natural selection. Favoring players with higher fitness, the latter is key for understanding the challenges faced by cooperators when competing with defectors. Evolutionary game theory provides a competent theoretical framework for addressing the subtleties of cooperation in such situations, which are known as social dilemmas. Recent advances point towards the fact that the evolution of strategies alone may be insufficient to fully exploit the benefits offered by cooperative behavior. Indeed, while spatial structure and heterogeneity, for example, have been recognized as potent promoters of cooperation, coevolutionary rules can extend the potentials of such entities further, and even more importantly, lead to the understanding of their emergence. The introduction of coevolutionary rules to evolutionary games implies, that besides the evolution of strategies, another property may simultaneously be subject to evolution as well. Coevolutionary rules may affect the interaction network, the reproduction capability of players, their reputation, mobility or age. Here we review recent works on evolutionary games incorporating coevolutionary rules, as well as give a didactic description of potential pitfalls and misconceptions associated with the subject. In addition, we briefly outline directions for future research that we feel are promising, thereby particularly focusing on dynamical effects of coevolutionary rules on the evolution of cooperation, which are still widely open to research and thus hold promise of exciting new discoveries.

Subfields: Ecology, Evolution, Behavior and Systematics, Genetics, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/86ad59cb0ff2ec9dce7e14187c5b639bfd637f78

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Citations in the corpus

Cyclic dominance in evolutionary games: a review (2014, background): “The topology of the interaction network may also change as a result of a particular coevolutionary rule, as studied f r quently before in the realm of social dilemma games (see [28] for a review).”
Life is Physics: Evolution as a Collective Phenomenon Far From Equilibrium (2010, background): “Typically players update their strategy based upon their interactions with their network neighbours during the game, representing perhaps the simplest game theory models where there is feedback between the environment and the agents[192].”
Identifying Influential Nodes in Large-Scale Directed Networks: The Role of Clustering (2013, background): “The density of interactions among neighbors can be characterized by the local clustering coefficient [21], which has great impacts on network dynamics, such as game theory [12,13,22–24], cascading [25], synchronization [26,27] and spreading [28–31].”
Evolutionary dynamics of group interactions on structured populations: a review (2013, background): “Possibilities seem endless, as re cently reviewed for games governed by pairwise interactions [136] .”
Emotional Multiagent Reinforcement Learning in Spatial Social Dilemmas (2015, background): “Most of these mechanisms, however, are based on the Evolutionary Game Theory (EGT) [5], [6], with a focus either on the macrolevel population dynamics using replicator functions or on the agent-level strategy dynamics based on predefined imitatio n rules.”
Heterogeneous Aspirations Promote Cooperation in the Prisoner's Dilemma Game (2010, background): “Although in our simulations we never quite reach the ‘‘best takes all’’ limit, and thus a direct comparison with the seminal works is somewhat circumstantial, we find here that the intermediate regions of heterogenous aspirations offer fascinating new insights into the evolution of cooperation, and ”
A hybrid multi-stage stochastic programming-robust optimization model for maximizing the supply chain of a forest-based biomass power plant considering uncertainties (2016, methodology): “Barring technological breakthroughs, modeling based on game theory have been considered (for an introduction see Perc and Szolnoki (2010), Wang et al. (2015), Perc (2006, 2007)).”
Evolution of Cooperation in Multiplex Networks (2012, background): “[18] Perc, M.”
Metric-based resolvability of polycyclic aromatic hydrocarbons (2021, background): “Metric dimension is extensively applied in the various fields of science such as facility location problems, sonar and coastguard Loran [42], computer networks [28], combinatorial optimization [39], robot navigation [23], pharmaceutical chemistry [6], weighing problems [43], and image processing, fo”