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Beyond rational monotony: some strong non-horn rules for nonmonotonic inference relations
1997
Journal of Logic and Computation
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Lehmann, Magidor and others have investigated the e ects of adding the non-Horn rule of rational monotony to the rules for preferential inference in nonmonotonic reasoning. ...
Finally, we consider brie y some curious Horn rules beyond the preferential ones but weaker than monotony, notably those which we call conjunctive insistence and n-monotony. ...
Acknowledgements We would like to thank Michael Freund for very penetrating comments on several versions of this work and for the unpublished observations cited as personal communications in the text. ...
doi:10.1093/logcom/7.5.605
fatcat:23otjmtqpbbdhme3fg75bdgkji
Page 7534 of Mathematical Reviews Vol. , Issue 98M
[page]
1998
Mathematical Reviews
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rational monotony: some strong non-Horn rules for nonmonotonic inference reiations. ...
In this paper a number of non-Horn rules for inference in non- monotonic reasoning that are stronger than or incomparable with rational monotony (if a+ £ and at/7y, then aA yt f#), but are weaker than ...
Logical questions behind the lottery and preface paradoxes: lossy rules for uncertain inference
2011
Synthese
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We reflect on lessons that the lottery and preface paradoxes provide for the logic of uncertain inference. ...
relations without that rule, the study of other rules that may nevertheless be satisfied in its absence, and a partial rehabilitation of conjunction as a 'lossy' rule. ...
Acknowledgements Thanks to an anonymous referee who pressed for a lower bound on iterated better than one first provided, Jim Hawthorne for collaborating on the product lower bounds for CT and in ...
doi:10.1007/s11229-011-9997-2
fatcat:enfh4zfg5zhqxdpsswd6n2rlgq
El dilema de Jorgensen: la búsqueda de los fundamentos semánticos para los imperativos
2016
PHAINOMENON
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Let us see,
Classical logic Classical Monotony ((Σ⊆Δ)˄(Σ⊢Γ)) ⇒ (Δ⊢Γ)
Non-monotonic logics Rational Monotony 1 ((Δ⊬¬φ)˄(Δ⊢ψ)) ⇒ ((Δ˄φ)⊢ψ) Cautious Monotony ((Δ⊢φ)˄(Δ⊢ψ)) ⇒ (Δ˄φ)⊢ψ) Roughly, classical ...
well-formed formulae and semantics, and, Q: is the rules of inference. ...
Thus, we think Horn 2 is not tenable anymore, at least, it is not as strong as it was in 1938. ...
doi:10.33539/phai.v15i1.98
fatcat:w7iqg373b5hrxpasot2vu5unx4
Chapter 6 Nonmonotonic Reasoning
[chapter]
2008
Foundations of Artificial Intelligence
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Acknowledgments We would like to thank Vladimir Lifschitz and Hudson Turner for helpful comments and suggestions. ...
Theorem 27 An inference relation is rational if and only if it is preferential and satisfies Rational Monotony. ...
The resulting relation does not in general satisfy Rational monotony, a property that arguably all bona fide nonmonotonic inference relations should satisfy. ...
doi:10.1016/s1574-6526(07)03006-4
fatcat:7r4l7tqgn5hfjok7yqbuxj5xwa
Dynamics of Belief: Abduction, Horn Knowledge Base And Database Updates
[article]
2015
arXiv
pre-print
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Such a generalization of belief dynamics, referred to as base dynamics, is presented in this paper, along with the concept of a generalized revision algorithm for knowledge bases (Horn or Horn logic with ...
The present paper provides a comparative study of view update algorithms in rational approach. ...
Definition 39 (Update magic set rule satisfying strong minimality). ...
arXiv:1501.06206v2
fatcat:ktavsd2e5nf57lkv4wxbxzk4rq
From Shallow to Deep Interactions Between Knowledge Representation, Reasoning and Machine Learning (Kay R. Amel group)
[article]
2019
arXiv
pre-print
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Then some methodologies combining reasoning and learning are reviewed (such as inductive logic programming, neuro-symbolic reasoning, formal concept analysis, rule-based representations and ML, uncertainty ...
Some common concerns are identified and discussed such as the types of used representation, the roles of knowledge and data, the lack or the excess of information, or the need for explanations and causal ...
Then the rules discovered are genuine default rules that can be reused in a nonmonotonic inference system, and can be encoded in possibilistic logic (assuming rational monotony for the inference relation ...
arXiv:1912.06612v1
fatcat:yfnx3pzs6jhxtggaylc76pwjc4
Qualitative probabilities for default reasoning, belief revision, and causal modeling
1996
Artificial Intelligence
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Inferences are supported by a unique priority ordering on rules which is syntactically derived from the knowledge base. ...
Practical algorithms are developed and analyzed for testing consistency, computing rule ordering, and answering queries. ...
Acknowledgements We thank Ernest Adams, Craig Boutilier, Nir Friedman, Hector Geffner, and Kurt Konolige for insightful discussions on related topics and an anonymous reviewer for helpful comments on a ...
doi:10.1016/0004-3702(95)00090-9
fatcat:vfq7s4r5rfbpbbd5esue4tpei4
On properties of update sequences based on causal rejection
2002
Theory and Practice of Logic Programming
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Moreover, some new properties for approaches to updating logic programs are considered as well. ...
For this purpose, we review postulates and principles for update and revision operators which have been proposed in the area of theory change and nonmonotonic reasoning. ...
for their useful remarks and corrections. ...
doi:10.1017/s1471068401001247
fatcat:ah3j3kk6tjauvbvh5jgww5irr4
On Properties of Update Sequences Based on Causal Rejection
[article]
2001
arXiv
pre-print
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We review postulates for update and revision operators from the area of theory change and nonmonotonic reasoning, and some new properties are considered as well. ...
New information is incorporated into the current knowledge base subject to a causal rejection principle enforcing that, in case of conflicts, more recent rules are preferred and older rules are overridden ...
for their useful remarks and corrections. ...
arXiv:cs/0109006v1
fatcat:lgiuthpwx5fsngn32esqgapvze
A Knowledge Level Account of Forgetting
2017
The Journal of Artificial Intelligence Research
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Moreover, the approach clarifies the relation between forgetting and related operations, including belief contraction. ...
This view also leads to insights with respect to specific logics: for example, forgetting in first-order logic is somewhat different from the accepted approach. ...
I thank a second reviewer for helpful comments, particularly with regards to work in answer set programmming. ...
doi:10.1613/jair.5530
fatcat:wvidqe2ukfbodkhuzssikq4upy
Edited transcription of the workshop on defeasible reasoning with specificity and multiple inheritance St. Louis, April 1989
1990
ACM SIGART Bulletin
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We could consistently assert for example, birds fly, and yet Opus is a bird that doesn't fly. On the other hand, we do get some non-trivial relations. ...
A lot of results show that major frameworks for dealing with the problems of non-monotonieity, ranging from probability to preference over models, have a lot in common. ...
doi:10.1145/122388.122389
fatcat:xqpkc37n75biheym7vydc6w5zi
Combining probabilistic logic programming with the power of maximum entropy
2004
Artificial Intelligence
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They both also satisfy the property of rational monotonicity and several irrelevance properties. ...
We then analyze the nonmonotonic behavior of both approaches along benchmark examples and along general properties for default reasoning from conditional knowledge bases. ...
One way to explain the reasonableness of maximum entropy inference is to investigate its formal properties according to widely accepted standards for nonmonotonic inference relations, such as System ¤ ...
doi:10.1016/j.artint.2004.04.003
fatcat:avc3lq4eibahjkmj5fi2cgxg6m
Page 1619 of Mathematical Reviews Vol. , Issue Index
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Mathematical Reviews
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(English summary) (see 98c:68016)
Bezzazi, Hassan (with Makinson, David; Pino Pérez, Ramén) Beyond rational monotony: some strong non-Horn rules for nonmonotonic inference relations. ...
., 984:68192
Georgatos, Konstantinos Ordering-based representations of rational inference. ...
Page 82 of Mathematical Reviews Vol. , Issue Index
[page]
Mathematical Reviews
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(Russian) 98i:03033
Béziau, Jean-Yves sce Krause, Décio, 98h:03037
Bezzazi, Hassan (with Makinson, David; Pino Pérez, Ramon) Beyond rational monotony some strong non-Horn rules for nonmonotonic inference ...
relations. ...
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