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  1. On the complexity of inconsistency measurement.Matthias Thimm & Johannes P. Wallner - 2019 - Artificial Intelligence 275 (C):411-456.
  • First-order logical filtering.Afsaneh Shirazi & Eyal Amir - 2011 - Artificial Intelligence 175 (1):193-219.
  • A theory of change for prioritised resilient and evolvable software systems.Giuseppe Primiero, Franco Raimondi & Taolue Chen - 2019 - Synthese 198 (S23):5719-5744.
    The process of completing, correcting and prioritising specifications is an essential but very complex task for the maintenance and improvement of software systems. The preservation of functionalities and the ability to accommodate changes are main objectives of the software development cycle to guarantee system reliability. Logical theories able to fully model such processes are still insufficient. In this paper we propose a full formalisation of such operations on software systems inspired by the Alchourrón–Gärdenfors–Makinson paradigm for belief revision of human epistemic (...)
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  • Revision operators with compact representations.Pavlos Peppas, Mary-Anne Williams & Grigoris Antoniou - 2024 - Artificial Intelligence 329 (C):104080.
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  • Plan reuse versus plan generation: a theoretical and empirical analysis.Bernhard Nebel & Jana Koehler - 1995 - Artificial Intelligence 76 (1-2):427-454.
  • On knowledge evolution: acquisition, revision, contraction.Eliezer L. Lozinskii - 1997 - Journal of Applied Non-Classical Logics 7 (1-2):177-211.
    ABSTRACT We consider evolution of knowledge bases caused by a sequence of basic steps of acquisition of a new information, either consistent or inconsistent with the original system. To make this process comply with the Principe of Minimal Change, a special evidence metric is introduced for measuring distance between states of knowledge. Then a novel semantics of knowledge bases is developed suggested by the heuristics of weighted maximally consistent subsets. The latter is efficiently applied to the processes of consistent and (...)
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  • Foundations of instance level updates in expressive description logics.Hongkai Liu, Carsten Lutz, Maja Miličić & Frank Wolter - 2011 - Artificial Intelligence 175 (18):2170-2197.
  • The complexity of belief update.Paolo Liberatore - 2000 - Artificial Intelligence 119 (1-2):141-190.
  • Reducing belief revision to circumscription.Paolo Liberatore & Marco Schaerf - 1997 - Artificial Intelligence 93 (1-2):261-296.
  • Reasoning under inconsistency: A forgetting-based approach.Jérôme Lang & Pierre Marquis - 2010 - Artificial Intelligence 174 (12-13):799-823.
  • DA2 merging operators.S. Konieczny, J. Lang & P. Marquis - 2004 - Artificial Intelligence 157 (1-2):49-79.
  • Enhancing disjunctive logic programming systems by SAT checkers.Christoph Koch, Nicola Leone & Gerald Pfeifer - 2003 - Artificial Intelligence 151 (1-2):177-212.
  • On the measure of conflicts: Shapley Inconsistency Values.Anthony Hunter & Sébastien Konieczny - 2010 - Artificial Intelligence 174 (14):1007-1026.
  • Propositional belief base update and minimal change.Andreas Herzig & Omar Rifi - 1999 - Artificial Intelligence 115 (1):107-138.
  • The complexity of theory revision.Russell Greiner - 1999 - Artificial Intelligence 107 (2):175-217.
  • Cumulative default logic: Finite characterization, algorithms, and complexity.Georg Gottlob & Mingyi Zhang - 1994 - Artificial Intelligence 69 (1-2):329-345.
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  • AGM 25 Years: Twenty-Five Years of Research in Belief Change.Eduardo Fermé & Sven Ove Hansson - 2011 - Journal of Philosophical Logic 40 (2):295 - 331.
    The 1985 paper by Carlos Alchourrón (1931–1996), Peter Gärdenfors, and David Makinson (AGM), "On the Logic of Theory Change: Partial Meet Contraction and Revision Functions" was the starting-point of a large and rapidly growing literature that employs formal models in the investigation of changes in belief states and databases. In this review, the first twentyfive years of this development are summarized. The topics covered include equivalent characterizations of AGM operations, extended representations of the belief states, change operators not included in (...)
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  • AGM 25 Years: Twenty-Five Years of Research in Belief Change.Eduardo Fermé & Sven Ove Hansson - 2011 - Journal of Philosophical Logic 40 (2):295-331.
    The 1985 paper by Carlos Alchourrón, Peter Gärdenfors, and David Makinson, “On the Logic of Theory Change: Partial Meet Contraction and Revision Functions” was the starting-point of a large and rapidly growing literature that employs formal models in the investigation of changes in belief states and databases. In this review, the first twenty-five years of this development are summarized. The topics covered include equivalent characterizations of AGM operations, extended representations of the belief states, change operators not included in the original (...)
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  • Sound and efficient closed-world reasoning for planning.Oren Etzioni, Keith Golden & Daniel S. Weld - 1997 - Artificial Intelligence 89 (1-2):113-148.
  • Semantics and complexity of abduction from default theories.Thomas Eiter, Georg Gottlob & Nicola Leone - 1997 - Artificial Intelligence 90 (1-2):177-223.
  • Updating action domain descriptions.Thomas Eiter, Esra Erdem, Michael Fink & Ján Senko - 2010 - Artificial Intelligence 174 (15):1172-1221.
  • Default reasoning from conditional knowledge bases: Complexity and tractable cases.Thomas Eiter & Thomas Lukasiewicz - 2000 - Artificial Intelligence 124 (2):169-241.
  • Belief revision in Horn theories.James P. Delgrande & Pavlos Peppas - 2015 - Artificial Intelligence 218 (C):1-22.
  • A consistency-based approach for belief change.James P. Delgrande & Torsten Schaub - 2003 - Artificial Intelligence 151 (1-2):1-41.
  • On the Tractable Counting of Theory Models and its Application to Truth Maintenance and Belief Revision.Adnan Darwiche - 2001 - Journal of Applied Non-Classical Logics 11 (1-2):11-34.
    We address in this paper the problem of counting the models of a propositional theory under incremental changes to its literals. Specifcally, we show that if a propositional theory Δ is in a special form that we call smooth, deterministic, decomposable negation normal form, then for any consistent set of literals S, we can simultaneously count the models of Δ ∪ S and the models of every theory Δ ∪ T where T results from adding, removing or flipping a literal (...)
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  • A comprehensive semantic framework for data integration systems.Andrea Calì, Domenico Lembo & Riccardo Rosati - 2005 - Journal of Applied Logic 3 (2):308-328.
  • The size of a revised knowledge base.Marco Cadoli, Francesco M. Donini, Paolo Liberatore & Marco Schaerf - 1999 - Artificial Intelligence 115 (1):25-64.
  • Fixpoint semantics for active integrity constraints.Bart Bogaerts & Luís Cruz-Filipe - 2018 - Artificial Intelligence 255 (C):43-70.
  • Weakening conflicting information for iterated revision and knowledge integration.Salem Benferhat, Souhila Kaci, Daniel Le Berre & Mary-Anne Williams - 2004 - Artificial Intelligence 153 (1-2):339-371.
  • Logical representation and fusion of prioritized information based on guaranteed possibility measures: Application to the distance-based merging of classical bases.Salem Benferhat & Souhila Kaci - 2003 - Artificial Intelligence 148 (1-2):291-333.
  • Proof Theory of Finite-valued Logics.Richard Zach - 1993 - Dissertation, Technische Universität Wien
    The proof theory of many-valued systems has not been investigated to an extent comparable to the work done on axiomatizatbility of many-valued logics. Proof theory requires appropriate formalisms, such as sequent calculus, natural deduction, and tableaux for classical (and intuitionistic) logic. One particular method for systematically obtaining calculi for all finite-valued logics was invented independently by several researchers, with slight variations in design and presentation. The main aim of this report is to develop the proof theory of finite-valued first order (...)
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