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The resource view on vigilance performance was tested. First, a low demanding task was compared with a similar low demanding task in which stimulus presentation was less monotonous due to added, irrelevant, stimuli. The resource view, maintaining that vigilance is lowered by hard mental work, predicts that addition of irrelevant stimuli will not affect(More)
Vigilance is assumed to decline with sustained task performance. The EEG-effects during performance on mental tasks, however, cannot be ascribed indisputably to vigilance decline per se. During task performance itself, effects of information processing and vigilance decline may be confounded. In this study, effects of sustained mental effort were studied in(More)
Both physical and mental effort are thought to affect vigilance. Mental effort is known for its vigilance declining effects, but the effects of physical effort are less clear. This study investigated whether these two forms of effort affect the EEG and subjective alertness differently. Participants performed a physical task and were subsequently presented(More)
Narcolepsy is associated with lowered vigilance. Diurnal variation in vigilance appears altered, but the exact nature of this change is unclear. It was hypothesized that the homeostatic sleep drive is increased in narcolepsy. Decreased levels of vigilance are reflected in low frequency band power in the electroencephalogram (EEG), so these frequencies were(More)
Collaboration environments impose high demands on humans and artificial systems. Especially during critical tasks team members, including humans, artificial systems and other (sub-) teams, require support to guarantee their continued effectiveness. Effectiveness of individuals and teams is an important ingredient for organizational effectiveness, managerial(More)
Research on multi-agent systems often involves experiments, also in situations where humans interact with agents. Consequently, the field of experimental (human) sciences becomes more and more relevant. This paper clarifies how things can and often <i>do</i> go wrong in distributed AI experiments. We show the flaws in methodological design in existing(More)
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