Narrow Results

In some practical situations – e.g., when treating a new illness – we do not have enough data to make valid statistical conclusions. In such situations, it is necessary to use expert knowledge – and thus, it is beneficial to use fuzzy techniques that were specifically designed to process such knowledge. At first glance, it may seem that in situations when we have large amounts of data, the relative importance of expert knowledge should decrease. However, somewhat surprisingly, it turns out that expert knowledge is still very useful in the current age of big data. In this paper, we explain how exactly (and why) expert knowledge is useful, and we overview efficient methods for processing this knowledge. This overview is illustrated by examples from environmental science, geosciences, engineering (in particular, aircraft maintenance and underwater robots), and medicine.

A low-cost, biologically inspired underwater walking robot (see Fig. 1) has been designed and built to covertly explore the seabed and to determine properties of submerged objects in obscure and inaccessible underwater locations. This paper focuses on a preliminary evaluation of an artificial active whisker to instrument this platform. Results demonstrate that both range and bearing to objects contacted by the whisker can be determined using simple data driven heuristics.