Interdisciplinary Framework for Integrating Artificial Intelligence based Fuzzy System history and Psychology Exploring Core knowledge using Decision Making Process
Abstract
Human decision-making cannot be explained without referring to several fields such as artificial intelligence (AI), history, and psychology. This paper postulates an interdisciplinary model which incorporates the use of AI systems based on fuzzy logic and psychological concepts of human thought combined with past historical trends of human behaviour. A fuzzy inference model is developed using a dataset of past cases of decision, cognitive variables and fuzzy scores annotated by experts to analyse the effects of core knowledge structures on decision outcomes. Empirical analysis based on machine-learning-powered fuzzy modelling demonstrates that the hybrid architecture is better in terms of interpretability, contextual reasoning, and predictive accuracy compared to conventional analytic models. The results are that AI-based fuzzy reasoning may fill the gaps between the past and our cognitive psychology, increasing our knowledge of making decisions in uncertain settings. This framework of behavioural predictions, policy development, and cognitive decision making can be expanded in future studies.