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Independence and Possibilistic Conditioning

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Abstract

There is not a unique definition of a conditional possibility distribution since the concept of conditioning is complex and many papers have been conducted to define conditioning in a possibilistic framework. In most cases, independence has been also defined and studied by means of a kind of analogy with the probabilistic case. In [2,4], we introduce conditional possibility as a primitive concept by means of a function whose domain is a set of conditional events. In this paper, we define a concept of independence associated with this form of conditional possibility and we show that classical properties required for independence concepts are satisfied.

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Authors and Affiliations

  1. LIP6, Pôle IA, Université Paris VI, 8 rue du Capitaine Scott, 75015, Paris, France

    Bernadette Bouchon-Meunier & Christophe Marsala

  2. Dipartimento di Matematica, Università di Perugia, 06100, Perugia, Italy

    Giulianella Coletti

Authors
  1. Bernadette Bouchon-Meunier
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  2. Giulianella Coletti
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  3. Christophe Marsala
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Bouchon-Meunier, B., Coletti, G. & Marsala, C. Independence and Possibilistic Conditioning. Annals of Mathematics and Artificial Intelligence 35, 107–123 (2002). https://doi.org/10.1023/A:1014579015954

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