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

Volume 24, Number 2-3, May 2000

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