Our Neuro-Cognitive Modeling Group is mainly motivated by the question: "How does the mind work?". We pursue an integrative, interdisciplinary, functional, and computational approach. We try to steer our research towards supporting healthy, sustainable, and enjoyable world development.
Our main premise is that our brain is an inference system, which dynamically learns and develops event-predictive, probabilistic structures. Via these structures it actively infers – and thus generates and controls – current attention, thoughts, and behaviors. Its goal is to maintain internal homeostasis. As a result, it strives to flexibly behave socially and adaptively in our highly complex socio-cultural environments.
To corroborate evidence, and to shed light on the details behind, we conduct behavioral studies in the real world as well as in virtual realities, including language production and interpretation studies. Moreover, we are building artificial, Bayesian and deep – typically recurrent – generative neural network models. We use the models to probe our integrative theoretical assumptions and to develop useful, truly artificially intelligent systems. Meanwhile, we advance computational theories of machine learning. We foster the development of dynamically unfolding, learning, and decision making processes (concurrently). We study inductive learning and processing biases to focus learning progress on critical environmental structures and causal interactions between them.
We integrate our research into further reaching aspects concerning human cognition, artificial intelligence, and research impacts on our societies and our world and environment. On the cognition side, these include the (reflexive and reflective) self, action decision making, planning, reasoning, social interaction, education, and language. On the AI side, these include the development of forecasting systems in the geosciences – including water discharge, erosion, substance advection and diffusion, weather, and climate – as well as the development of causal forecasting systems, explainable AI, language understanding, and strong AI. On the environmental side, these include the analysis and prevention of spreading false beliefs and other forms of manipulation as well as approaches to support a healthy and sustainable development of our world, where it is worth living in for all of us.
Introducing Cognitive Science from a Functional and Computational Perspective:
Please check the Book Errata for two corrections.