Pawlak: rough sets
In October 1982 Zdzisław Pawlak of the Institute of Computer Science of the Polish Academy of Sciences published 'Rough Sets', on approximate operations on sets, approximate equality and approximate inclusion. The author presents the approach as an alternative to fuzzy set theory and tolerance theory and as a mathematical foundation for artificial intelligence: classification, inductive reasoning, pattern recognition.
Why it matters
Imprecise knowledge gained another formal language, separate from probability and fuzzy sets: a set is described by a pair of approximations that the available information can tell apart. This is an editorial assessment.
The paper was received in June 1981 and revised in September 1982. Its first page lists among the key words artificial intelligence, learning algorithms and pattern recognition; on the second the author says he aims at mathematical foundations for artificial intelligence rather than a new set theory, and that he was inspired by Michalski's results on automatic classification. Reference 7 is ICS PAS Report 431 (1981), where the notion was introduced; the report itself was not found. In 2002 Pawlak wrote that the theory overlaps with fuzzy sets and Bayesian inference but is an independent, complementary, not competing discipline. What the record does not claim: any application or measurement; the paper only outlines applications.