Automatic Process Model Generation for Cognitive Modeling

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The goal of this project is to achieve a paradigm shift in the cognitive modeling of human reasoning processes, which has so far focused on cognitive theories for aggregated responses. By identifying and evaluating subcomponents and atomic processes of existing theories and formalizing the space of cognitive operations in which specific parameters for interindividual differences are integrated, we aim to generate cognitive process models in an automated manner that can achieve high predictive performance and adaptively adjust to the individual, thus allowing for individualized cognitive modeling of human inference, and thus represents a solution to the problems identified in the state of the art and identified potential for improvement in current inference research. Since the focus of component recombination is on predictive power, and the method is thus free of additional theoretical assumptions, it can be guaranteed that the cognitive processes are selected solely on the basis of their actual added value for the process model.