The haunted swamps of heuristics: Uncertainty in problem solving

Artem Amirkhanov, Stefan Bruckner, Christoph Heinzl, Eduard Gröller

Research output: Chapter in Book/Report/Conference proceedingsChapterpeer-review


In scientific visualization the key task of research is the provision of insight into a problem. Finding the solution to a problem may be seen as finding a path through some rugged terrain which contains mountains, chasms, swamps, and few flatlands. This path—an algorithm discovered by the researcher—helps users to easily move around this unknown area. If this way is a wide road paved with stones it will be used for a long time by many travelers. However, a narrow footpath leading through deep forests and deadly swamps will attract only a few adventure seekers. There are many different paths with different levels of comfort, length, and stability, which are uncertain during the research process. Finding a systematic way to deal with this uncertainty can greatly assist the search for a safe path which is in our case the development of a suitable visualization algorithm for a specific problem. In this work we will analyze the sources of uncertainty in heuristically solving visualization problems and will propose directions to handle these uncertainties.

Original languageEnglish
Title of host publicationScientific Visualization
Subtitle of host publicationUncertainty, Multifield, Biomedical, and Scalable Visualization
Number of pages10
Publication statusPublished - 2014

Publication series

NameMathematics and Visualization
ISSN (Print)1612-3786


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