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COLLECTIF

Philosophy of probability

  • Pages : XIV-291
  • Collection : Philosophical Studies Series (Kluwer)
  •  
  • Support : Print [Hardback edition]
  • Edition : Original
  • Ville : Dordrecht
  •  
  • ISBN : 0-7923-2385-8
  •  
  • Date de création : 04-01-2011
  • Dernière mise à jour : 03-10-2015

Résumé :

Anglais

Eleven contributions : 1: Personalistic Bayesianism; C. Howson. 2: On Higher Order Beliefs; N.-E. Sahlin. 3: On the Logic of Relevance; P. Gr̃denfors. 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. – They intend to provide a comprehensive introduction to theoretical issues that occupy a central position in disciplines ranging from philosophy of mind and epistemology to cognitive science, decision theory and artificial intelligence. Some contributions shed new light on the standard conceptions of probability (such as Bayesianism, logical and computational theories); others offer detailed analyses of two important topics in the field of cognitive science : – the meaning and the representation of (partial) belief, and – the management of uncertaincy . This multidisciplinary approach to probability (the authors are philosophers as well as computer scientists) is designed to illuminate the intricacies of the problems in the domain of cognitive inquiry. M.-M. V.

 

Résumé :

Anglais

Eleven contributions : 1: Personalistic Bayesianism; C. Howson. 2: On Higher Order Beliefs; N.-E. Sahlin. 3: On the Logic of Relevance; P. Gr̃denfors. 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. – They intend to provide a comprehensive introduction to theoretical issues that occupy a central position in disciplines ranging from philosophy of mind and epistemology to cognitive science, decision theory and artificial intelligence. Some contributions shed new light on the standard conceptions of probability (such as Bayesianism, logical and computational theories); others offer detailed analyses of two important topics in the field of cognitive science : – the meaning and the representation of (partial) belief, and – the management of uncertaincy . This multidisciplinary approach to probability (the authors are philosophers as well as computer scientists) is designed to illuminate the intricacies of the problems in the domain of cognitive inquiry. M.-M. V.

 

Articles :

pages 1 à 12

Personalistic Bayesianism

HOWSON Colin

pages 13 à 34

On higher order beliefs

SAHLIN Nils-Eric

pages 35 à 54

On the logic of relevance

GÄRDENFORS Peter

pages 55 à 77

Diverging distributions

MILLER David William

pages 79 à 108

Inductive logic revisited

DUBUCS Jacques

pages 109 à 127

Probability and utility

VICKERS John M.

pages 129 à 143

What has probability to do with strenght of belief

COHEN L. Jonathan

pages 145 à 167

Randomness, unpredictability and absence of order : the identification by the theory of recursivity of the mathematical notion of random sequence

DELAHAYE Jean-Paul

pages 169 à 222

A glance at non-standard models and logics of uncertainty and vagueness

DUBOIS Didier, PRADE Henri

pages 223 à 255

Casual laws are objectifications of inductive schemes

SPOHN Wolfgang

pages 257 à 291

Probabilistic inference in artificial intelligence : the method of bayesian networks

GOLMARD Jean-Louis

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