International Journal of Approximate Reasoning, Volume 24

Volume 24, Number 1, April 2000

• Ramón Sangüesa, Ulises Cortés:
  New perspectives on Causal Networks: the first CaNew workshop. 1-10
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• Luis M. de Campos, Juan F. Huete:
  A new approach for learning belief networks using independence criteria. 11-37
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• Robert Castelo, Arno Siebes:
  Priors on network structures. Biasing the search for Bayesian networks. 39-57
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• Armelle Fay, Jean-Yves Jaffray:
  A justification of local conditioning in Bayesian networks. 59-81
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• Beatriz Lacruz, Pilar Lasala, Alberto Lekuona:
  Graphical dynamic linear models: specification, use and graphical transformations. 83-102
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• Ramón Sangüesa, Ulises Cortés:
  Prior knowledge for learning networks in non-probabilistic settings. 103-120
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Volume 24, Number 2-3, May 2000

• Fabio Gagliardi Cozman, Serafín Moral:
  Reasoning with imprecise probabilities. 121-123
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• Peter Walley:
  Towards a unified theory of imprecise probability. 125-148
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• Kurt Weichselberger:
  The theory of interval-probability as a unifying concept for uncertainty. 149-170
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• Pierre Hansen, Brigitte Jaumard, Marcus Poggi de Aragão, Fabien Chauny, Sylvain Perron:
  Probabilistic satisfiability with imprecise probabilities. 171-189
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• Fabio Gagliardi Cozman:
  Computing posterior upper expectations. 191-205
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• Andrea Capotorti, Barbara Vantaggi:
  Axiomatic characterization of partial ordinal relations. 207-219
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• Sujoy Mukerji:
  A survey of some applications of the idea of ambiguity aversion in economics. 221-234
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• Paolo Vicig:
  Epistemic independence for imprecise probabilities. 235-250
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• Veronica Biazzo, Angelo Gilio:
  A generalization of the fundamental theorem of de Finetti for imprecise conditional probability assessments. 251-272
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• Dieter Denneberg:
  Totally monotone core and products of monotone measures. 273-281
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• Alain Chateauneuf, Jean-Christophe Vergnaud:
  Ambiguity reduction through new statistical data. 283-299
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