Systems, Algorithms, and Cognitive Models to Predict Individual Human Reasoning (PREDIR)

• Applicant: Professor Dr. Marco Ragni
• Subject Area: Image and Language Processing, Computer Graphics and Visualisation, Human Computer Interaction, Ubiquitous and Wearable Computing
• Term: since 2016
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 283135041

This project focuses on a central challenge of cognitive AI research: to develop a system that is able to predict an individual's information processing and in particular future conclusions of based on few observed examples. By focusing on the individual, this project differs from approaches in, for example, cognitive psychology, which, due to statistical, data-analytical reasons, disregards deviant behavior of individual experimental participants and thus focuses only on cognitive models for aggregated experimental data and identification of general cognitive phenomena. In this project, we reanalyze data with a focus on an individual perspective, develop computational systems capable of predicting an individual's future conclusions given sparse background information, and analyze and evaluate the performance of existing approaches in cognitive psychology, cognitive science, and data-driven methods such as recommender systems. In particular, we will identify and then develop and systematically improve methods that enable accurate predictions but also identify data-driven upper bounds. Furthermore, the question of which mechanisms underlie human reasoning and how these insights can be reflected in an automatic development of adaptive cognitive modeling approaches will be clarified. This project develops cognitive AI models that are able to adaptively and predictively adjust to individual thought processes and predict conclusions.

• DFG Programme: Research Grants