Stability of strategies in payoff-driven evolutionary games on networks
Francesco Sorrentino, Nicholas Mecholsky

TL;DR
This paper models how strategies evolve in a network of agents playing Prisoner's Dilemma, revealing that network structure and payoff parameters influence the emergence of polarized cooperation or defection.
Contribution
It introduces a nonlinear deterministic model for strategy evolution considering payoff-driven decisions with limited information in networked Prisoner's Dilemma games.
Findings
Polarized strategies emerge in sparse, heterogeneous, and assortative networks.
High benefits of cooperation promote polarized strategies.
Network structure critically influences strategy stability.
Abstract
We consider a network of coupled agents playing the Prisoner's Dilemma game, in which players are allowed to pick a strategy in the interval [0,1], with 0 corresponding to defection, 1 to cooperation, and intermediate values representing mixed strategies in which each player may act as a cooperator or a defector over a large number of interactions with a certain probability. Our model is payoff-driven, i.e., we assume that the level of accumulated payoff at each node is a relevant parameter in the selection of strategies. Also, we consider that each player chooses his/her strategy in a context of limited information. We present a deterministic nonlinear model for the evolution of strategies. We show that the final strategies depend on the network structure and on the choice of the parameters of the game. We find that polarized strategies (pure cooperator/defector states) typically…
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