ML Anthology

The Persistence of Derived Information

Karen L. Myers, David E. Smith
AAAI 1988 pp. 496-500
/aaai/1988/myers1988aaai-persistence/

Abstract

Work on the problem of reasoning about change has focussed on the persistence of nonderived information, while neglecting the effects of inference within individual states. In this paper, we illustrate how such inferences add a new dimension of complexity to reasoning about change and show that failure to allow for such inferences can result in an unwarranted loss of derived information. The difficulties arise with a class of deductions having the property that their conclusions should be allowed to persist even though some components of the justifications involved may no longer be valid. We describe this notion of components of a justification being inessential to the persistence of that justification. A solution to the persistence problem is presented in terms of a default frame axiom that is sensitive to both justification information and specifications of inessentiality. 1

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Text

Myers and Smith. "The Persistence of Derived Information." AAAI Conference on Artificial Intelligence, 1988.

Markdown

[Myers and Smith. "The Persistence of Derived Information." AAAI Conference on Artificial Intelligence, 1988.](https://mlanthology.org/aaai/1988/myers1988aaai-persistence/)

BibTeX

@inproceedings{myers1988aaai-persistence,
  title     = {{The Persistence of Derived Information}},
  author    = {Myers, Karen L. and Smith, David E.},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {1988},
  pages     = {496-500},
  url       = {https://mlanthology.org/aaai/1988/myers1988aaai-persistence/}
}