Modeling and optimization of networked evolutionary game based on incomplete information with switched topologies
Yalin Gui,
Lixin Gao,
Zhitao Li
Abstract:In the realm of evolutionary game theory, the majority of scenarios involve players with incomplete knowledge, specially regarding their opponents' actions and payoffs compounded by the ever‐shifting landscape of players' interactions. These dynamics present formidable challenges in both the analysis and optimization of game evolution. To address this, a novel model named the networked evolutionary game (NEG) is proposed based on incomplete information with switched topologies. This model captures situations w… Show more
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