Common Sense and Maximum Entropy

被引:0
作者
Jeff Paris
机构
[1] University Manchester,Department of Mathematics Manchester
来源
Synthese | 1998年 / 117卷
关键词
Probability Function; Common Sense; Maximum Entropy; Propositional Variable; Inference Process;
D O I
暂无
中图分类号
学科分类号
摘要
This paper concerns the question of how to draw inferences common sensically from uncertain knowledge. Since the early work of Shore and Johnson (1980), Paris and Vencovská (1990), and Csiszár (1989), it has been known that the Maximum Entropy Inference Process is the only inference process which obeys certain common sense principles of uncertain reasoning. In this paper we consider the present status of this result and argue that within the rather narrow context in which we work this complete and consistent mode of uncertain reasoning is actually characterised by the observance of just a single common sense principle (or slogan).
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页码:75 / 93
页数:18
相关论文
共 8 条
[1]  
Maung I.(1990)A Note on the Infeasibility of Some Inference Processes International Journal of Intelligent Systems 5 595-604
[2]  
Paris J. B.(1990)A Note on the Inevitability of Maximum Entropy International Journal of Approximate Reasoning 4 183-224
[3]  
Paris J. B.(1997)In Defence of the Maximum Entropy Inference Process International Journal of Approximate Reasoning 17 77-103
[4]  
Vencovská A.(1980)Axiomatic Derivation of the Principle of Maximum Entropy and the Principle of Minimum Cross-Entropy IEEE Transactions on Information Theory IT-26 26-37
[5]  
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[6]  
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[7]  
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[8]  
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