Nonmonotonic consequences in default domain theory
dc.contributor.author | Zhang, Guo‐qiang | en_US |
dc.contributor.author | Rounds, William C. | en_US |
dc.date.accessioned | 2006-09-08T19:37:16Z | |
dc.date.available | 2006-09-08T19:37:16Z | |
dc.date.issued | 1997-03 | en_US |
dc.identifier.citation | Zhang, Guo‐Qiang; Rounds, William C.; (1997). "Nonmonotonic consequences in default domain theory." Annals of Mathematics and Artificial Intelligence 20 (1-4): 227-265. <http://hdl.handle.net/2027.42/41772> | en_US |
dc.identifier.issn | 1012-2443 | en_US |
dc.identifier.issn | 1573-7470 | en_US |
dc.identifier.uri | https://hdl.handle.net/2027.42/41772 | |
dc.description.abstract | Default domain theory is a framework for representing and reasoning about commonsense knowledge. Although this theory is motivated by ideas in Reiter’s work on default logic, it is in some sense a dual framework. We make Reiter’s default extension operator into a constructive method of building models, not theories. Domain theory, which is a well established tool for representing partial information in the semantics of programming languages, is adopted as the basis for constructing partial models. This paper considers some of the laws of nonmonotonic consequence, due to Gabbay and to Kraus, Lehmann, and Magidor, in the light of default domain theory. We remark that in some cases Gabbay’s law of cautious monotony is open to question. We consider an axiomatization of the nonmonotonic consequence relation on prime open sets in the Scott topology – the natural logic – of a domain, which omits this law. We prove a representation theorem showing that such relations are in one to one correspondence with the consequence relations determined by extensions in Scott domains augmented with default sets. This means that defaults are very expressive: they can, in a sense, represent any reasonable nonmonotonic entailment. Results about what kind of defaults determine cautious monotony are also discussed. In particular, we show that the property of unique extensions guarantees cautious monotony, and we give several classes of default structures which determine unique extensions. | en_US |
dc.format.extent | 413834 bytes | |
dc.format.extent | 3115 bytes | |
dc.format.mimetype | application/pdf | |
dc.format.mimetype | text/plain | |
dc.language.iso | en_US | |
dc.publisher | Kluwer Academic Publishers; Springer Science+Business Media | en_US |
dc.subject.other | Computer Science | en_US |
dc.subject.other | Computer Science, General | en_US |
dc.subject.other | Artificial Intelligence (Incl. Robotics) | en_US |
dc.subject.other | Mathematics, General | en_US |
dc.subject.other | Nonlinear Dynamics, Complex Systems, Chaos, Neural Networks | en_US |
dc.title | Nonmonotonic consequences in default domain theory | en_US |
dc.type | Article | en_US |
dc.subject.hlbsecondlevel | Computer Science | en_US |
dc.subject.hlbsecondlevel | Science (General) | en_US |
dc.subject.hlbtoplevel | Science | en_US |
dc.subject.hlbtoplevel | Engineering | en_US |
dc.description.peerreviewed | Peer Reviewed | en_US |
dc.contributor.affiliationum | Artificial Intelligence Laboratory, University of Michigan, Ann Arbor, Michigan, 48109, USA | en_US |
dc.contributor.affiliationother | Department of Computer Science, University of Georgia, Athens, Georgia, 30602, USA | en_US |
dc.contributor.affiliationumcampus | Ann Arbor | en_US |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/41772/1/10472_2004_Article_325432.pdf | en_US |
dc.identifier.doi | http://dx.doi.org/10.1023/A:1018988629376 | en_US |
dc.identifier.source | Annals of Mathematics and Artificial Intelligence | en_US |
dc.owningcollname | Interdisciplinary and Peer-Reviewed |
Files in this item
Remediation of Harmful Language
The University of Michigan Library aims to describe library materials in a way that respects the people and communities who create, use, and are represented in our collections. Report harmful or offensive language in catalog records, finding aids, or elsewhere in our collections anonymously through our metadata feedback form. More information at Remediation of Harmful Language.
Accessibility
If you are unable to use this file in its current format, please select the Contact Us link and we can modify it to make it more accessible to you.