How automation level influences moral decisions of humans collaborating with industrial robots in different scenarios.

Introduction: Digitalization in intelligent manufacturing leads to the development of Industry 4.0/5.0 and human-cyber-physical systems.

Information stored in memory affects abductive reasoning.

Abductive reasoning describes the process of deriving an explanation from given observations. The theory of abductive reasoning (TAR; Johnson and Krems, Cognitive Science 25:903-939, 2001) assumes that when information is presented sequentially, new information is integrated into a mental representation, a situation model, the central data structure on which all reasoning processes are based. Because working memory capacity is limited, the question arises how reasoning might change with the amount of information that has to be processed in memory.

Tracing current explanations in memory: A process analysis based on eye-tracking.

Sequential abductive reasoning is the process of finding the best explanation for a set of observations. Explanations can be multicausal and require the retrieval of previously found ones from memory. The theory of abductive reasoning (TAR) allows detailed predictions on what information is stored and retrieved from memory during reasoning.

Covert shifts of attention can account for the functional role of "eye movements to nothing".

When trying to remember verbal information from memory, people look at spatial locations that have been associated with visual stimuli during encoding, even when the visual stimuli are no longer present. It has been shown that such "eye movements to nothing" can influence retrieval performance for verbal information, but the mechanism underlying this functional relationship is unclear. More precisely, covert in comparison to overt shifts of attention could be sufficient to elicit the observed differences in retrieval performance.