Probabilistic inferences from conjoined to iterated conditionals

被引:21
|
作者
Sanfilippo, Giuseppe [1 ]
Pfeifer, Niki [2 ]
Over, David E. [3 ]
Gilio, Angelo [4 ]
机构
[1] Dept Math & Comp Sci, Via Archirafi 34, I-90123 Palermo, Italy
[2] Ludwig Maximilians Univ Munchen, Munich Ctr Math Philosophy, Ludwigstr 31, D-80539 Munich, Germany
[3] Univ Durham, Dept Psychol, Sci Site,South Rd, Durham DH1 3LE, England
[4] Univ Roma La Sapienza, Dept Basic & Appl Sci Engn, Via A Scarpa 14, I-00161 Rome, Italy
关键词
QUASI CONJUNCTION; LIKELIHOOD FUNCTIONS; COHERENCE; DISJUNCTION; UNCERTAINTY; ENTAILMENT; PSYCHOLOGY; OPPOSITION;
D O I
10.1016/j.ijar.2017.10.027
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
There is wide support in logic, philosophy, and psychology for the hypothesis that the probability of the indicative conditional of natural language, P(if A then B), is the conditional probability of B given A, P(B|A). We identify a conditional which is such that P(if A then B) = P(B|A) with de Finetti's conditional event, B|A. An objection to making this identification in the past was that it appeared unclear how to form compounds and iterations of conditional events. In this paper, we illustrate how to overcome this objection with a probabilistic analysis, based on coherence, of these compounds and iterations. We interpret the compounds and iterations as conditional random quantities which, given some logical dependencies, may reduce to conditional events. We show how the inference to B|A from A and B can be extended to compounds and iterations of both conditional events and biconditional events. Moreover, we determine the respective uncertainty propagation rules. Finally, we make some comments on extending our analysis to counterfactuals. (C) 2017 Elsevier Inc. All rights reserved.
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页码:103 / 118
页数:16
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