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Profile: Didier Dubois
  1.  14
    From Blanché's Hexagonal Organization of Concepts to Formal Concept Analysis and Possibility Theory.Didier Dubois & Henri Prade - 2012 - Logica Universalis 6 (1-2):149-169.
    The paper first introduces a cube of opposition that associates the traditional square of opposition with the dual square obtained by Piaget’s reciprocation. It is then pointed out that Blanché’s extension of the square-of-opposition structure into an conceptual hexagonal structure always relies on an abstract tripartition. Considering quadripartitions leads to organize the 16 binary connectives into a regular tetrahedron. Lastly, the cube of opposition, once interpreted in modal terms, is shown to account for a recent generalization of formal concept analysis, (...)
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  2.  25
    Some Syntactic Approaches to the Handling of Inconsistent Knowledge Bases: A Comparative Study Part 1: The Flat Case.Salem Benferhat, Didier Dubois & Henri Prade - 1997 - Studia Logica 58 (1):17-45.
    This paper presents and discusses several methods for reasoning from inconsistent knowledge bases. A so-called argued consequence relation, taking into account the existence of consistent arguments in favour of a conclusion and the absence of consistent arguments in favour of its contrary, is particularly investigated. Flat knowledge bases, i.e., without any priority between their elements, are studied under different inconsistency-tolerant consequence relations, namely the so-called argumentative, free, universal, existential, cardinality-based, and paraconsistent consequence relations. The syntax-sensitivity of these consequence relations is (...)
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  3.  13
    Fuzzy Sets and Systems: Theory and Applications.Didier DuBois - 1997 - Academic Press.
    / Part INTRODUCTION Fuzziness is not a priori an obvious concept and demands some explanation. "Fuzziness" is what Black (NF) calls "vagueness" when ...
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  4. Three-Valued Logics for Incomplete Information and Epistemic Logic.Davide Ciucci & Didier Dubois - 2012 - In Luis Farinas del Cerro, Andreas Herzig & Jerome Mengin (eds.), Logics in Artificial Intelligence. Springer. pp. 147--159.
  5.  1
    On Ignorance and Contradiction Considered as Truth-Values.Didier Dubois - 2008 - Logic Journal of the IGPL 16 (1):195--216.
    A critical view of the alleged significance of Belnap four-valued logic for reasoning under inconsistent and incomplete information is provided. The difficulty lies in the confusion between truth-values and information states, when reasoning about Boolean propositions. So our critique is along the lines of previous debates on the relevance of many-valued logics and especially of the extension of the Boolean truth-tables to more than two values as a tool for reasoning about uncertainty. The critique also questions the significance of partial (...)
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  6.  22
    Qualitative Heuristics For Balancing the Pros and Cons.Jean-François Bonnefon, Didier Dubois, Hélène Fargier & Sylvie Leblois - 2008 - Theory and Decision 65 (1):71-95.
    Balancing the pros and cons of two options is undoubtedly a very appealing decision procedure, but one that has received scarce scientific attention so far, either formally or empirically. We describe a formal framework for pros and cons decisions, where the arguments under consideration can be of varying importance, but whose importance cannot be precisely quantified. We then define eight heuristics for balancing these pros and cons, and compare the predictions of these to the choices made by 62 human participants (...)
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  7.  2
    Accepted Beliefs, Revision and Bipolarity in the Possibilistic Framework.Didier Dubois & Henri Prade - 2009 - In Franz Huber & Christoph Schmidt-Petri (eds.), Degrees of Belief. Springer. pp. 161--184.
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  8.  48
    Knowledge-Driven Versus Data-Driven Logics.Didier Dubois, Petr Hájek & Henri Prade - 2000 - Journal of Logic, Language and Information 9 (1):65--89.
    The starting point of this work is the gap between two distinct traditions in information engineering: knowledge representation and data - driven modelling. The first tradition emphasizes logic as a tool for representing beliefs held by an agent. The second tradition claims that the main source of knowledge is made of observed data, and generally does not use logic as a modelling tool. However, the emergence of fuzzy logic has blurred the boundaries between these two traditions by putting forward fuzzy (...)
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  9.  31
    A Practical Approach to Revising Prioritized Knowledge Bases.Salem Benferhat, Didier Dubois, Henri Prade & Mary-Anne Williams - 2002 - Studia Logica 70 (1):105-130.
    This paper investigates simple syntactic methods for revising prioritized belief bases, that are semantically meaningful in the frameworks of possibility theory and of Spohn''s ordinal conditional functions. Here, revising prioritized belief bases amounts to conditioning a distribution function on interpretations. The input information leading to the revision of a knowledge base can be sure or uncertain. Different types of scales for priorities are allowed: finite vs. infinite, numerical vs. ordinal. Syntactic revision is envisaged here as a process which transforms a (...)
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  10.  1
    Author’s Response to Wansing and Belnap’s Generalized Truth-Values.Didier Dubois - 2010 - Logic Journal of the IGPL 18 (6):936-940.
  11.  4
    The Strength of Desires: A Logical Approach.Didier Dubois, Emiliano Lorini & Henri Prade - 2017 - Minds and Machines 27 (1):199-231.
    The aim of this paper is to propose a formal approach to reasoning about desires, understood as logical propositions which we would be pleased to make true, also acknowledging the fact that desire is a matter of degree. It is first shown that, at the static level, desires should satisfy certain principles that differ from those to which beliefs obey. In this sense, from a static perspective, the logic of desires is different from the logic of beliefs. While the accumulation (...)
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  12.  16
    Vérité incertaine – Vérité approximative.Didier Dubois & Henri Prade - 2001 - Rue Descartes 1 (1):105-126.
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  13.  35
    Suitable Properties for Any Electronic Voting System.Jean-Luc Koning & Didier Dubois - 2006 - Artificial Intelligence and Law 14 (4):251-260.
    Numerous countries are heading toward digital infrastructures. In particular this new technology promises to help support methods for elections. However, one should be careful that such an infrastructure does not hinder the voting and representation issues. On the contrary, it should support those issues and help citizens have a clearer picture of the underlying mechanisms. This paper deals with the limits of voting procedures as they are described in classical collective choice theory and reflects on ways to aggregate electronic votes (...)
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  14.  12
    Multiple Agent Possibilistic Logic.Asma Belhadi, Didier Dubois, Faiza Khellaf-Haned & Henri Prade - 2013 - Journal of Applied Non-Classical Logics 23 (4):299-320.
  15. Belief Structures, Possibility Theory and Decomposable Confidence Measures on Finite Sets.Didier Dubois - 1986 - Computers and Artificial Intelligence (5):403--416.
     
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  16.  6
    An Overview of Bipolar Qualitative Decision Rules.Jean-Francois Bonnefon, Didier Dubois & Hélène Fargier - 2008 - In Giacomo Della Riccia, Didier Dubois & Hans-Joachim Lenz (eds.), Preferences and Similarities. Springer. pp. 47--73.
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  17.  2
    Vérité Incertaine? Vérité Approximative.Didier Dubois & Henri Prade - 2001 - Rue Descartes 31 (1):105.
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  18.  1
    Possibilistic Reasoning with Partially Ordered Beliefs.Fayçal Touazi, Claudette Cayrol & Didier Dubois - 2015 - Journal of Applied Logic 13 (4):770-798.
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  19.  2
    Inference in Possibilistic Hypergraphs.Didier Dubois & Henri Prade - 1991 - In B. Bouchon-Meunier, R. R. Yager & L. A. Zadeh (eds.), Uncertainty in Knowledge Bases. Springer. pp. 249--259.
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  20.  1
    A Glance at Non-Standard Models and Logics of Uncertainty and Vagueness.Didier Dubois & Henri Prade - 1993 - In J. Dubucs (ed.), Philosophy of Probability. Kluwer, Dordrecht. pp. 169--222.
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  21.  1
    Indian Institute of Technology, Kanpur January 14–26, 2008.Ramon Jansana, Mai Gehrke, Alessandra Palmigiano, Mihir K. Chakraborty, Didier Dubois, Eric Pacuit, Rohit Parikh & Prakash Panangaden - 2008 - Bulletin of Symbolic Logic 14 (4).
  22. Preferences and Similarities.Giacomo Della Riccia, Didier Dubois & Hans-Joachim Lenz (eds.) - 2008 - Springer.
  23. Fuzzy Sets, Logics, and Reasoning About Knowledge.Didier Dubois, Henri M. Prade & E. P. Klement - 1999
     
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  24. New Trends and Open Problems in Fuzzy Logic and Approximate Reasoning.Didier Dubois & Henri Prade - 1996 - Theoria: Revista de Teoría, Historia y Fundamentos de la Ciencia 11 (3):109-121.
    This short paper about fuzzy set-based approximate reasoning first emphasizes the three main semantics for fuzzy sets: similarity, preference and uncertainty. The difference between truth-functional many-valued logics of vague or gradual propositions and non fully compositional calculi such as possibilistic logic or similarity logics is stressed. Then, potentials of fuzzy set-based reasoning methods are briefly outlined for various kinds of approximate reasoning: deductive reasoning about flexible constraints, reasoning under uncertainty and inconsistency, hypothetical reasoning, exception-tolerant plausible reasoning using generic knowledge, interpolative (...)
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