scholarly journals Nonmonotonic Reasoning, Expectations Orderings, and Conceptual Spaces

Author(s):  
Matías Osta-Vélez ◽  
Peter Gärdenfors

AbstractIn Gärdenfors and Makinson (Artif Intell 65(2):197–245, 1994) and Gärdenfors (Knowledge representation and reasoning under uncertainty, Springer-Verlag, 1992) it was shown that it is possible to model nonmonotonic inference using a classical consequence relation plus an expectation-based ordering of formulas. In this article, we argue that this framework can be significantly enriched by adopting a conceptual spaces-based analysis of the role of expectations in reasoning. In particular, we show that this can solve various epistemological issues that surround nonmonotonic and default logics. We propose some formal criteria for constructing and updating expectation orderings based on conceptual spaces, and we explain how to apply them to nonmonotonic reasoning about objects and properties.

Author(s):  
Grigoris Antoniou

This paper discusses the significance of nonmonotonic reasoning, a method from the knowledge representation area, to mainstream software engineering. In particular, we discuss why the use of defaults in specifications is an adequate way of addressing some of the most important problems in requirements engineering, such as: The problem of identifying and dealing with inconsistencies; evolving system requirements; requirements prioritization; and the quality of specifications with respect to naturalness and compactness. We argue that these problems need to be addressed in a principled, formal way, and that default reasoning provides adequate mechanisms to deal with them.


1994 ◽  
Vol 9 (4) ◽  
pp. 399-416 ◽  
Author(s):  
Didier Duboid ◽  
Henri Prade

AbstractThis paper provides a survey of the state of the art in plausible reasoning, that is exception tolerant reasoning under incomplete information. Three requirements are necessary for a formalism in order to cope with this problem: (i) making a clear distinction between factual information and generic knowledge; (ii) having a correct representation of partial ignorance; (iii) providing a nonmonotonic inference mechanism. Classical logic fails on requirements (i) and (iii), whilst the Bayesian approach does not fulfil (ii) in an unbiased way. In this perspective, various uncertainty modelling frameworks are reviewed: MYCIN-like fully compositional calculi, belief functions, upper and lower probability systems, and possibility theory. Possibility theory enables classical logic to be extended to layered sets of formulae, where layers express certainty levels. Finally, it is explained how generic knowledge can be expressed by constraints on possibility measures, and how possibilistic inferences can encode nonmonotonic reasoning in agreement with the Lehmann et al. postulates.


2014 ◽  
Author(s):  
David Braines ◽  
Geeth de Mel ◽  
Chris Gwilliams ◽  
Christos Parizas ◽  
Diego Pizzocaro ◽  
...  

1990 ◽  
Vol 2 (3) ◽  
pp. 287-301 ◽  
Author(s):  
Michael V. Mannino ◽  
Betsy S. Greenberg ◽  
Sa Neung Hong

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