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  1. Asma Belhadi, Didier Dubois, Faiza Khellaf-Haned & Henri Prade (2013). Multiple Agent Possibilistic Logic. Journal of Applied Non-Classical Logics 23 (4):299-320.
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  2. Davide Ciucci & Didier Dubois (2012). Three-Valued Logics for Incomplete Information and Epistemic Logic. In. In Luis Farinas del Cerro, Andreas Herzig & Jerome Mengin (eds.), Logics in Artificial Intelligence. Springer. 147--159.
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  3. Didier Dubois & Henri Prade (2012). From Blanché's Hexagonal Organization of Concepts to Formal Concept Analysis and Possibility Theory. 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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  4. Didier Dubois & Henri Prade (2009). Accepted Beliefs, Revision and Bipolarity in the Possibilistic Framework. In. In Franz Huber & Christoph Schmidt-Petri (eds.), Degrees of Belief. Springer. 161--184.
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  5. Jean-Francois Bonnefon, Didier Dubois & Hélène Fargier (2008). An Overview of Bipolar Qualitative Decision Rules. In. In Giacomo Della Riccia, Didier Dubois & Hans-Joachim Lenz (eds.), Preferences and Similarities. Springer. 47--73.
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  6. Jean-François Bonnefon, Didier Dubois, Hélène Fargier & Sylvie Leblois (2008). Qualitative Heuristics For Balancing the Pros and Cons. 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. Ramon Jansana, Mai Gehrke, Alessandra Palmigiano, Mihir K. Chakraborty, Didier Dubois, Eric Pacuit, Rohit Parikh & Prakash Panangaden (2008). Indian Institute of Technology, Kanpur January 14–26, 2008. Bulletin of Symbolic Logic 14 (4).
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  8. Jean-Luc Koning & Didier Dubois (2006). Suitable Properties for Any Electronic Voting System. 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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  9. Salem Benferhat, Didier Dubois, Henri Prade & Mary-Anne Williams (2002). A Practical Approach to Revising Prioritized Knowledge Bases. 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. Didier Dubois & Henri Prade (2001). Vérité incertaine – Vérité approximative. Rue Descartes 1 (1):105-126.
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  11. Didier Dubois, Petr Hájek & Henri Prade (2000). Knowledge-Driven Versus Data-Driven Logics. 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 rules as (...)
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  12. Salem Benferhat, Didier Dubois & Henri Prade (1997). Some Syntactic Approaches to the Handling of Inconsistent Knowledge Bases: A Comparative Study Part 1: The Flat Case. 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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  13. Didier Dubois & Henri Prade (1996). New Trends and Open Problems in Fuzzy Logic and Approximate Reasoning. Theoria 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 (which handles uncertainty) 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 (...)
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  14. Didier Dubois & Henri Prade (1993). A Glance at Non-Standard Models and Logics of Uncertainty and Vagueness. In. In J. Dubucs (ed.), Philosophy of Probability. Kluwer, Dordrecht. 169--222.
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  15. Didier Dubois & Henri Prade (1991). Inference in Possibilistic Hypergraphs. In B. Bouchon-Meunier, R. R. Yager & L. A. Zadeh (eds.), Uncertainty in Knowledge Bases. Springer. 249--259.
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