2019
DOI: 10.1016/j.amc.2018.09.034
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Aspiration driven coevolution resolves social dilemmas in networks

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Cited by 31 publications
(8 citation statements)
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“…In recent years, the coevolution of player strategy and network structure has been studied as an important mechanism that promotes cooperation. Many forms and driving factors of coevolution have been studied extensively [26,49,50,52], including reputation [26,52]. Reputation is a non-revenue reward for players who choose to cooperate during evolution, and becomes a social attribute.…”
Section: Conclusion and Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…In recent years, the coevolution of player strategy and network structure has been studied as an important mechanism that promotes cooperation. Many forms and driving factors of coevolution have been studied extensively [26,49,50,52], including reputation [26,52]. Reputation is a non-revenue reward for players who choose to cooperate during evolution, and becomes a social attribute.…”
Section: Conclusion and Discussionmentioning
confidence: 99%
“…The coevolutionary game can be driven by aspiration [49,50] or empathy [51], reputation [26,52]. Reputation has been shown to have a strong influence on cooperative results in dynamic games [26], which models indirect reciprocity in human societies.…”
Section: Introductionmentioning
confidence: 99%
“…Previous theoretical studies aiming to model the evolution of social norms mainly fall into two categories [50]: (1) game-theoretical models and (2) opinion dynamics models. The gametheoretical models concentrate on the question of how the commitment to one specific norm can be reached in the presence of social dilemma, such as cooperation norm [39,49,[51][52][53][54] or coordination norm [2,55]. The opinion dynamics models attempt to understand how one of several possible behavior can establish a norm [56][57][58].…”
Section: Discussionmentioning
confidence: 99%
“…As long as the game revenue-cost ratio is higher than network connectivity, reciprocity and multistep prediction horizon are necessary for stable collaboration and sufficient for fixed cooperation [14]. e facilitation of cooperative behaviour mainly depends on participants' weight distribution, which is based on the formation of cooperative clusters controlled by highweight collaborators [15]. e system's general description is derived using ordinary differential equations, which provides a common framework to simulate and quantify the effects of single-node dynamics on the macroscopic state of the network [16].…”
Section: Introductionmentioning
confidence: 99%