The global geopolitical landscape is characterized by the rise of new powers and a shift toward multipolarity. This study examines the impact of multipolarity on international cooperation using an iterated game theory approach, particularly the classic prisoner’s dilemma, extended to a multiplayer setting. This effort can be regarded as a preliminary study of hypothetical optimal global cooperation. The main hypothesis is that an increase in the number of large countries in the international system will lead to higher levels of cooperation. Our simulation approach confirmed this. Our findings extend to the conclusion that multipolarity, under appropriate cultural and value systems, can foster new economic development and fair competition. Furthermore, we emphasize the importance of evolving strategies and cooperative dynamics in a multipolar world, contributing to discussions on foreign economic policy integration, sustainability, and managing vulnerabilities among great powers. The study underscores the necessity of strategic frameworks and international institutions in promoting global stability and cooperation amidst the complexities of multipolarity.

VAT is one of the most important sources of the public revenues in the EU Member States; therefore, it is crucial to determine the factors of VAT collection. So far, only a few researchers analyzed the influence of individual economic sectors ...

Strategic foresight often involves navigating deeply uncertain futures through scenario-based reasoning. Traditional methods rely on static narratives or probabilistic models, which fail to capture the dynamic, interacting, and nonexclusive nature of competing futures. This paper introduces a quantum-inspired framework for scenario interaction grounded in the mathematical formalism of superposition, interference, and contextuality. Agents are modeled as epistemic learners who iteratively update their preferences across multiple narrative pathways, which are treated as basis states in a conceptual Hilbert space. The simulation combines reinforcement learning with stochastic imitation, producing emergent distributions that resemble quantum-like collapse under feedback. Central to the model is the emergence of symmetries in the scenario structure and learning dynamics. Agents begin with neutral priors, facing a balanced reward landscape, epistemic and normative symmetry that is gradually broken through adaptive behavior. However, statistical symmetries persist at the ensemble level, as agents maintain partial preferences and oscillate among futures. These layered symmetries reflect both the cognitive realism of foresight practices and the mathematical tractability of quantum-inspired systems. The proposed model bridges strategic foresight, game-theoretic interaction, and quantum cognition, and offers a novel computational lens to study how futures are constructed, selected, and stabilized under uncertainty.