Title :
Inherently imprecise causal complexes
Author :
Mazlack, Lawrence J.
Author_Institution :
Appl. Artificial Intell. Lab., Univ. of Cincinnati, Cincinnati, OH, USA
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;
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
DOI :
10.1109/NAFIPS.2010.5548411