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H-Complexity Metric for Qualitative Spatial and Temporal Reasoning Applications
 

Summary: H-Complexity Metric for
Qualitative Spatial and Temporal Reasoning Applications
Carl Schultz, Robert Amor
Department of Computer Science, The University of Auckland
Private Bag 92019, Auckland, New Zealand
csch050@aucklanduni.ac.nz, trebor@cs.auckland.ac.nz
Hans Guesgen
School of Engineering and Advanced Technology, Massey University
Private Bag 11222, Palmerston North, New Zealand
h.w.guesgen@massey.ac.nz
Abstract
Commonsense reasoning, in particular qualitative spatial
and temporal reasoning (QSTR), provides flexible and
intuitive methods for reasoning about vague and uncertain
information including temporal duration and ordering, and
spatial orientation, topology and distance. Despite
significant theoretical advances in QSTR, there is a distinct
absence of applications that employ these methods. The
central problem is a lack of application-level standards and
metrics that developers can use to measure the effectiveness

  

Source: Amor, Robert - Department of Computer Science, University of Auckland

 

Collections: Computer Technologies and Information Sciences