A hybrid computational approach to anticipate individuals in sequential problem solving.

Human-awareness is an ever more important requirement for AI systems that are designed to assist humans with daily physical interactions and problem solving. This is especially true for patients that need support to stay as independent as possible. To be human-aware, an AI should be able to anticipate the intentions of the individual humans it interacts with, in order to understand the difficulties and limitations they are facing and to adapt accordingly.

Cognitive processing stages in mental rotation - How can cognitive modelling inform HsMM-EEG models?

The aspiration for insight into human cognitive processing has traditionally driven research in cognitive science. With methods such as the Hidden semi-Markov Model-Electroencephalography (HsMM-EEG) method, new approaches have been developed that help to understand the temporal structure of cognition by identifying temporally discrete processing stages. However, it remains challenging to assign concrete functional contributions by specific processing stages to the overall cognitive process.