Synopsis
Introduction. 1: Personalistic Bayesianism; C. Howson. 2: On Higher Order Beliefs; N.-E. Sahlin. 3: On the Logic of Relevance; P. Gärdenfors. 4: Diverging Distributions; D. Miller. 5: Inductive Logic Revisited; J.-P. Dubucs. 6: Probability and Utility; J.M. Vickers. 7: What has Probability to Do with Strength of Belief; L.J. Cohen. 8: Randomness, Unpredictability and Absence of Order: the Identification by the Theory of Recursivity of the Mathematical Notion of Random Sequence; J.-P. Delahaye. 9: A Glance at Non-Standard Models and Logics of Uncertainty and Vaguness; D. Dubois, H. Prade. 10: Causal Laws are Objectifications of Inductive Schemes; W. Spohn. 11. Probabilistic Inference in Artificial Intelligence: the Method of Bayesian networks; J.-L. Golmard.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
