1996
DOI: 10.1007/bf00712384
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Nonstandard set theories and information management

Abstract: The merits of set theory as a foundational tool in mathematics stimulate its use in various areas of artificial intelligence, in particular intelligent information systems. In this paper, a study of various nonstandard treatments of set theory from this perspective is offered. Applications of these alternative set theories to information or knowledge management are surveyed.

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Cited by 5 publications
(4 citation statements)
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“…Formally, a set of circular (coss-referent and recursive) definitions can be handled rigorously using non-well-founded set theories, see Aczel (1988), Barwise and Etchemendy (1987), and Barwise and Moss (1996). Computationally, circularly defined data sets can be represented, stored and manipulated using appropriate data structures, see Akman and Pakkan (1996), Iordanov (2010), and Pakkan and Akman (1995).…”
Section: Objects Are Tokens For Eigen-solutions: Precision Stabilitymentioning
confidence: 99%
“…Formally, a set of circular (coss-referent and recursive) definitions can be handled rigorously using non-well-founded set theories, see Aczel (1988), Barwise and Etchemendy (1987), and Barwise and Moss (1996). Computationally, circularly defined data sets can be represented, stored and manipulated using appropriate data structures, see Akman and Pakkan (1996), Iordanov (2010), and Pakkan and Akman (1995).…”
Section: Objects Are Tokens For Eigen-solutions: Precision Stabilitymentioning
confidence: 99%
“…In fact, every object that can be defined in AFA ends up being isomorphic to an element in the universe of ZFC. The only advantage in this change is that it simplifies the treatment of circularities, in particular those that arise in the use of information and knowledge [Akman- Pakkan 1996]. Using coalgebraic methods-i.e.…”
Section: Existence Of States Of the Worldmentioning
confidence: 99%
“…The entire program of research that Jon Barwise initiated on situation theory and related formalisms, based on his idea that logic is a branch of applied mathematics, is clearly an inspiration for the approach we follow here [Barwise-Etchemendy 1987], [Barwise-Moss 1996], [Barwise-Seligman 1997]. In computer science, the advantages of adopting set theories closer to common sense have been emphasized in [Pakkan-Akman 1994] [Akman- Pakkan 1996]. More recently, Jan Mycielski has presented a universal set theory in which the class of mathematical objects can be given physical interpretations [Mycielski 2006], [Mycielski 2007].…”
Section: Introductionmentioning
confidence: 99%
“…The variation in these predictions can be explained by a combination of the level of imprecision in the theory and by properties of the end-user's experiment. For instance, the latter source of variation is influenced by properties of the equipment, including the precision, accuracy, and resolution of measuring devices [16,17], and also error bounds for fundamental constants and calibration factors [18][19][20][21][22][23][24][25][26]. We propose to choose a pragmatic hypothesis in such a way that the imprecision in the end-user's predictions is mostly due to his experimental conditions and not due to the level of imprecision in the theory that he uses.…”
Section: Introductionmentioning
confidence: 99%