TY - CHAP
T1 - The haunted swamps of heuristics
T2 - Uncertainty in problem solving
AU - Amirkhanov, Artem
AU - Bruckner, Stefan
AU - Heinzl, Christoph
AU - Gröller, Eduard
N1 - Publisher Copyright:
© Springer-Verlag London 2014.
PY - 2014
Y1 - 2014
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84921389604&partnerID=8YFLogxK
U2 - 10.1007/978-1-4471-6497-5_5
DO - 10.1007/978-1-4471-6497-5_5
M3 - Chapter
VL - 37
T3 - Mathematics and Visualization
SP - 51
EP - 60
BT - Scientific Visualization
PB - Springer
ER -