About Us
The ‘Computational Modelling in Psychology’ Chair at LMU was created in 2022 as part of the Bavarian High-Tech Agenda. We are a group of researchers interested in understanding cognition. That is, we want to know how people think, remember, decide, classify, reason, and explain. To create and develop such insights, we use a combination of formal modelling and experiments.
Mathematical and Computational Modelling
Theories are inescapably verbal, since they are a collection of claims about what is happening and how. Though we may be able to understand the consequences of any single idea, combining many ideas to form a theory can make things exceedingly difficult to intuit. Building a model helps us to understand our theories better. For example, we may better grasp the implications of our theories, or realise that some of our theory was missing, implicit, or ad hoc. Our lab tries to use formal models to improve our theories about human cognition.
Cognition
The fact that humans are intelligent leaves them with a practically limitless set of capacities. Our lab is interested in understanding what is fundamentally necessary for intelligence. For example, we want to know how people remember things over time, how people hold and work with multiple ideas at once, how perceptual input is turned into something actionable (e.g., how a traffic light can be identified as red or green), and how people create new knowledge.
Most aspects of human behaviour are not universal, but a product of the ideas embedded in a given culture, time, biology, upbringing, culture, etc. Such issues are still interesting because of their practical ramifications. For example, our lab is interested in questions such as when is thinking enjoyable, what makes some tasks difficult, how are interruptions disruptive, and when can decisions benefit from group discussion.
Machine Learning and Artificial Intelligence
The role of machine learning, automated systems, and so-called artificial intelligence (AI) in everyday life is about to explode. Our research group is concerned with two aspects of this new aspect of modern life.
First is the fundamental issue of intelligence. We need to improve our understanding of human cognition, because at present we cannot answer whether we should expect the current approaches in AI to ever yield truly intelligent behaviour. Our group wants to understand the ways in which human intelligence is different from things like chat bots, as well as what makes them appear similar.
Second is the practical question of how to facilitate human-machine interaction. Throughout history, people have typically relied on human experts for advice and information. Going forward, we should expect instead to hear such things from statistical/automated machines. The consequences for how humans can, and whether they should, incorporate such advice or information into their decisions will be one of the larger societal issues in the coming decades.