Reinforcement learning offers a promising approach for personalized, early-stage detection of behavioral events such as agitation in individuals with dementia, particularly when contextual insights from care staff are integrated. Given the scarcity and the ethical constraints of real-world agitation …

The generation of electrical power from renewable sources such as wind and solar power is on the rise. However, the nature of this power generation is characterized by a relatively high level of unpredictability, whereas the demand for electrical power continues to grow steadily. These factors – among …

Many product innovations can benefit from being more adaptive to their environment. Learning adaptive behavior can be time sensitive and complex. For that purpose we created a simulation environment with a reinforcement learning component for developing simple adaptive products. The environment models …

The security of online assessments is a major concern due to widespread cheating. One common form of cheating is impersonation, where students invite unauthorized persons to take assessments on their behalf. Several techniques exist to handle impersonation. Some researchers recommend use of integrity …

Background: Although physical activity (PA) has positive effects on health and well-being, physical inactivity is a worldwide problem. Mobile health interventions have been shown to be effective in promoting PA. Personalizing persuasive strategies improves intervention success and can be conducted using …

For people with early-dementia (PwD), it can be challenging to remember to eat and drink regularly and maintain a healthy independent living. Existing intelligent home technologies primarily focus on activity recognition but lack adaptive support. This research addresses this gap by developing an AI …

The number of applications in which industrial robots share their working environment with people is increasing. Robots appropriate for such applications are equipped with safety systems according to ISO/TS 15066:2016 and are often referred to as collaborative robots (cobots). Due to the nature of human-robot …

Key to reinforcement learning in multi-agent systems is the ability to exploit the fact that agents only directly influence only a small subset of the other agents. Such loose couplings are often modelled using a graphical model: a coordination graph. Finding an (approximately) optimal joint action for …

Industrial robot manipulators are widely used for repetitive applications that require high precision, like pick-and-place. In many cases, the movements of industrial robot manipulators are hard-coded or manually defined, and need to be adjusted if the objects being manipulated change position. To increase …

Dutch universities of applied sciences (UASs) had been teaching-only institutes since their legal origin in 1960. The development of higher education (HE) in Europe in the past twenty years requires UASs to embody and become hybrid organ-isations where education and research are integrated. Ever-changing, …