Cooperation, satisfaction, and decision uncertainty in social games on complex networks with aspiration-driven players

A network model based on players' aspirations is proposed and analyzed theoretically and numerically within the framework of evolutionary game theory. In this model, players decide whether to cooperate or defect by comparing their payoffs from pairwise games with their neighbors, driven by a common aspiration level. The model also incorporates a degree of stochasticity, or decision noise, through an effective temperature in the Fermi function. The level of cooperation in the system is fundamentally influenced by two social attributes: satisfaction, defined as the fraction of players whose payoffs exceed the aspiration level, and the degree of noise in decision-making. Deterministic players tend to maintain their initial strategies for sufficiently low aspiration levels, while the presence of noise promotes a state of perfect coexistence, resulting in half of the agents cooperating. The transition between these two behaviors can be critical, often leading to abrupt changes in cooperation levels. When the aspiration level is high, all players become dissatisfied, regardless of the effective temperature. Intermediate levels of aspiration lead to diverse behaviors, including sudden transitions for deterministic agents and a nonmonotonic relationship between cooperation and noise intensity. The study also carefully examines the effects of the interaction structure, initial conditions, and the strategy update rule (asynchronous versus synchronous). Special attention is given to the prisoner's dilemma, where significant cooperation levels can be achieved in a structured environment, with moderate aspiration and low decision noise intensity, and following a synchronous strategy updating scheme.