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2006 | OriginalPaper | Chapter

Maximum Entropy Inference for Geographical Information Systems

Authors : Hykel Hosni, Maria Vittoria Masserotti, Chiara Renso

Published in: Flexible Databases Supporting Imprecision and Uncertainty

Publisher: Springer Berlin Heidelberg

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An immediate problem in approaching GIS (Geographic Information Systems) consists in giving a sufficiently agreed definition of what GIS actually are. For present purposes it seems reasonable to consider GIS as being characterized by a twofold nature. On the one hand, GIS consist of a

technology

used for certain purposes. From this perspective, the crucial issues in GIS research amount to

computing

problems, both on the hardware and software level. On the other hand, however, GIS research is increasingly more focussed on

theoretical

issues concerning the representation of geographic information. According to the latter point of view GIS problems include, at the very least, issues of

knowledge representation and reasoning

. In this chapter we investigate some of the consequences deriving from approaching GIS from the latter point of view. In particular, we will be insisting on the fact that its s‘conceptual side’, so to speak, commits GIS research to achieving

scientific goals

which happen to be closely related to some of those pursued in Artificial Intelligence (AI) research.

3

In doing so, we adopt a perspective according to which GIS are essentially construed as artificial intelligent agents reasoning about a certain classes of natural environments.

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Metadata
Title
Maximum Entropy Inference for Geographical Information Systems
Authors
Hykel Hosni
Maria Vittoria Masserotti
Chiara Renso
Copyright Year
2006
Publisher
Springer Berlin Heidelberg
DOI
https://doi.org/10.1007/3-540-33289-8_11

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