• DocumentCode
    3533467
  • Title

    Inherently imprecise causal complexes

  • Author

    Mazlack, Lawrence J.

  • Author_Institution
    Appl. Artificial Intell. Lab., Univ. of Cincinnati, Cincinnati, OH, USA
  • fYear
    2010
  • fDate
    12-14 July 2010
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    Causal complexes are groupings of smaller causal relations that make up a large grained causal object. Usually, commonsense reasoning is more successful in reasoning about a few large-grained events than many fine-grained events. However, the larger-grained causal objects are necessarily more imprecise as some of their constituent components. Causality is imprecisely granular in many ways. Knowledge of at least some causal effects is inherently imprecise. It is unlikely that all possible factors can be known for many subjects; consequently, causal knowledge is inherently incomplete and therefore imprecise. A satisficing solution might be to develop large-grained solutions and then only go to the finer-grain when the impreciseness of the large-grain is unsatisfactory.
  • Keywords
    causality; common-sense reasoning; causal complexes; causal knowledge; causal relations; causality; commonsense reasoning; larger-grained causal objects; Artificial intelligence; Automobiles; Glass; Laboratories; Legged locomotion; Physics; Road accidents; causal; complexes; imprecise; inherent;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Information Processing Society (NAFIPS), 2010 Annual Meeting of the North American
  • Conference_Location
    Toronto, ON
  • Print_ISBN
    978-1-4244-7859-0
  • Electronic_ISBN
    978-1-4244-7857-6
  • Type

    conf

  • DOI
    10.1109/NAFIPS.2010.5548411
  • Filename
    5548411