Difference: ICA (2 vs. 3)

Revision 32007-01-03 - FabrizioMorbini

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Paper

Inheritance Comes of Age: Applying Nonmonotonic Techniques to Problems in Industry.
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  • find the maximally consistent subset made doing to union of the set of formulas linked to N_i and N and the set B.

2 problems:

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  • determining consistency is semi-decidable: consider only a subclass of formulas for which deciding consistency is decidable. But still, deciding consistency is intractable, ...
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  • determining consistency is semi-decidable: consider only a subclass of formulas for which deciding consistency is decidable. But still, deciding consistency is intractable. The author suggests a divide-and-conquer strategy: to compute consistency consider only the formulas belonging to a certain type. So, this implies that the formulas are dived into type of formulas (in the paper: administrative, medical, ...) and formulas in a type are always consistent with formulas in the other types.
 
  • there are more than 1 (typically) maximal subset. Which formula to remove: build a preference order.
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Observations (starting points for discussion)

Further readings

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The preference criteria are;
  • specificity: prefer more specific information. Given that bird fly and that Tweety (a bird) doesn't fly, then prefer the Tweety knowledge about flying instead of the generic bird knowledge because it is more specific to respect to Tweety.
  • order: when specificity doesn't help (multiple paths), then use the order O to choose which path to inherit from.

Open questions:

  • what to do with preempting paths. See figure 7 for an example.
  • determining conflicting paths can depend on knowledge. Therefore, it might be the case that in the network two path are not conflicting each other but given the background knowledge they are.

Why using this mixed representation mechanism instead of a either all-network or all-formulas approach? * converting everything to network goes against the principle that the nodes in a network represents concrete entities (now formulas would become nodes). Plus, the definition of inconsistency becomes difficult (because it depends on some property of paths not easily specifiable). * converting everything to formulas is not optimal because the distinction between taxonomic knowledge and general knowledge is lost. Plus efficient algorithms could be harder to write.

Conclusions:

  • check for problems for real world applications, use them instead of toy examples.
  • basic research is still needed
  • balance between basic reasearch and industrial collaboration
  • develop tools (not only on paper)
  • solving a real problem is typically harder and more complex than solving a toy problem.
 

-- FabrizioMorbini - 03 Jan 2007

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