Displaying similar documents to “Qualitative reasoning in Bayesian networks.”

Inference in conditional probability logic

Niki Pfeifer, Gernot D. Kleiter (2006)

Kybernetika

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An important field of probability logic is the investigation of inference rules that propagate point probabilities or, more generally, interval probabilities from premises to conclusions. Conditional probability logic (CPL) interprets the common sense expressions of the form “if ..., then ...” by conditional probabilities and not by the probability of the material implication. An inference rule is probabilistically informative if the coherent probability interval of its conclusion is...

(Pure) logic out of probability.

Ton Sales (1996)

Mathware and Soft Computing

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Today, Logic and Probability are mostly seen as independent fields with a separate history and set of foundations. Against this dominating perception, only a very few people (Laplace, Boole, Peirce) have suspected there was some affinity or relation between them. The truth is they have a considerable common ground which underlies the historical foundation of both disciplines and, in this century, has prompted notable thinkers as Reichenbach [14], Carnap [2] [3] or Popper [12] [13] (and...

Bayesian Propositional Logic

Tomasz Jarmużek, Mateusz Klonowski, Jacek Malinowski (2017)

Bulletin of the Section of Logic

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We define and investigate from a logical point of view a family of consequence relations defined in probabilistic terms. We call them relations of supporting, and write: |≈w where w is a probability function on a Boolean language. A |≈w B iff the fact that A is the case does not decrease a probability of being B the case. Finally, we examine the intersection of |≈w , for all w, and give some formal properties of it.

Knowledge revision in Markov networks.

Jörg Gebhardt, Christian Borgelt, Rudolf Kruse, Heinz Detmer (2004)

Mathware and Soft Computing

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A lot of research in graphical models has been devoted to developing correct and efficient evidence propagation methods, like join tree propagation or bucket elimination. With these methods it is possible to condition the represented probability distribution on given evidence, a reasoning process that is sometimes also called focusing. In practice, however, there is the additional need to revise the represented probability distribution in order to reflect some knowledge changes by satisfying...

Between logic and probability.

Ton Sales (1994)

Mathware and Soft Computing

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Logic and Probability, as theories, have been developed quite independently and, with a few exceptions (like Boole's), have largely ignored each other. And nevertheless they share a lot of similarities, as well a considerable common ground. The exploration of the shared concepts and their mathematical treatment and unification is here attempted following the lead of illustrious researchers (Reichenbach, Carnap, Popper, Gaifman, Scott & Krauss, Fenstad, Miller, David Lewis, Stalnaker,...