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Forbus, K. D. (1995). Qualitative spatial reasoning framework and frontiers. In Diagrammatic Reasoning, Glasgow, J., Narayanan, N. H. A., and Chandrasekaran, B., AAAI Press, 1995. pp 183--202.

@Article{,
  author = 	 {Forbus, K. D.},
  title = 	 {Qualitative spatial reasoning framework and
frontiers},
  year = 	 {1995},
}

Author of the summary: Jim Davies, 2001, jim@jimdavies.org

Cite this paper for:

This paper shows that for visual reasoning about physical systems, an agent needs both a metric diagram representation and a place vocabulary representation.

A metric diagram shows the quantitative aspects of the system, like sizes, as expressed in numbers, etc. Perceptual processes can be applied to it.

The place vocabulary is a qualitative representation of where things are and their shape, as is relevent to the task at hand. A place is a region of space where some important property (e.g. incontact with something) is constant.

Poverty conjecture: There is no problem-independent, purely qualitative representation of space or shape.

Qualitative representations break down: for example, you can represent that a robot can get through a certain door, but if he's carrying something, to figure it out you need to go to the metric level. [p186]

But the qualitative is important too, and the place vocabulary can make a graph of what the robot can do-- it's a task specific representation.

Thus, qualitative and quantitative information needs to be tightly coupled. [187]

FROB is a system that figured out the paths of balls on a landscape and whether they would collide. In FROB, a line segment has a pointer to a symbol (like a surface) as well as numerical info about length and end-points, etc. [189] The MD is necessary for precice predictions, and the PV allows for qualitative reasoning. FROB decomposes space along vertical and horizontal axes. [199]

Kim (1990): made a vocabulary for describing the behavior of fluid.

Summary author's notes:


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