A Cognitive Uncertainty Calculation Method Based on Probabilistic Linguistic Term Set and Applications in Geopolitical Risk Assessment

Risk is essentially uncertain, including objective uncertainty of natural attributes and subjective uncertainty of human cognition. The latter is associated with human cognitive thinking and social consciousness, making it challenging to quantify and articulate. Therefore, appropriately managing cognitive uncertainty is essential to achieve successful risk management. In situations involving political environments, decision-makers may rely on judgment or other qualitative information, which can be less reliable or more subjective. Therefore, using cognitive computing methods can provide significant benefits in quantifying and managing cognitive uncertainty. We propose a novel approach that utilizes a probabilistic linguistic quantification method for qualitative evaluation information. This method accounts for both the cognitive uncertainty and statistical uncertainty of decision-makers. To quantify the practical cognitive risk context in the risk evaluation, we propose a new probabilistic linguistic distance measure that quantifies the influence of experts’ subjective preference context in the risk environment. Furthermore, to represent both the risk-averse attitudes and the cognitive uncertainty context of the decision-makers, we propose an improved version of the prospect theory, which considers. This enables a more accurate representation of the practical cognitive decision-making processes. Subsequently, we construct a cognitive uncertainty evaluation model based on the probabilistic linguistic measurement and apply it to comprehensive risk assessment for geopolitical environments. Analysis of the risk assessment outcomes and comparative experiments indicate that the proposed methods can quantitatively assess and calculate decision-makers’ cognitive risk preferences while providing more accurate risk assessment outcomes. This study offers a novel and convenient tool to research risk evaluations focused on cognitive uncertainties.