12 found
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  1.  70
    On the Logic of Iterated Belief Revision.Adnan Darwiche & Judea Pearl - 1997 - Artificial Intelligence 89 (1-2):1-29.
    We show in this paper that the AGM postulates are too weak to ensure the rational preservation of conditional beliefs during belief revision, thus permitting improper responses to sequences of observations. We remedy this weakness by proposing four additional postulates, which are sound relative to a qualitative version of probabilistic conditioning. Contrary to the AGM framework, the proposed postulates characterize belief revision as a process which may depend on elements of an epistemic state that are not necessarily captured by a (...)
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  2.  16
    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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  3.  2
    On the Tractability of Counting Theory Models and its Application to Belief Revision and Truth Maintenance.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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  4.  11
    Open-World Probabilistic Databases: Semantics, Algorithms, Complexity.İsmail İlkan Ceylan, Adnan Darwiche & Guy Van den Broeck - 2021 - Artificial Intelligence 295:103474.
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  5. On Probabilistic Inference by Weighted Model Counting.Mark Chavira & Adnan Darwiche - 2008 - Artificial Intelligence 172 (6-7):772-799.
  6. On the Revision of Probabilistic Beliefs Using Uncertain Evidence.Hei Chan & Adnan Darwiche - 2005 - Artificial Intelligence 163 (1):67-90.
  7. A Logical Notion of Conditional Independence: Properties and Applications.Adnan Darwiche - 1997 - Artificial Intelligence 97 (1-2):45-82.
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  8. Compiling Propositional Weighted Bases.Adnan Darwiche & Pierre Marquis - 2004 - Artificial Intelligence 157 (1-2):81-113.
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  9. Recursive Conditioning.Adnan Darwiche - 2001 - Artificial Intelligence 126 (1-2):5-41.
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  10. A Differential Semantics for Jointree Algorithms.James D. Park & Adnan Darwiche - 2004 - Artificial Intelligence 156 (2):197-216.
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  11. On the Power of Clause-Learning SAT Solvers as Resolution Engines.Knot Pipatsrisawat & Adnan Darwiche - 2011 - Artificial Intelligence 175 (2):512-525.
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  12. Learning Bayesian Network Parameters Under Equivalence Constraints.Tiansheng Yao, Arthur Choi & Adnan Darwiche - 2017 - Artificial Intelligence 244:239-257.
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