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A linear programming framework for logics of uncertainty
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DOI：10.1016/0167-9236(94)00055-7.png)
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Several logics for reasoning under uncertainty distribute ''probability mass'' over sets in some sense. These include probabilistic logic, Dempster-Shafer theory, other logics based on belief functions, and second-order probabilistic logic. We show that these logics are instances of a certain type of linear programming model, typically with exponentially many variables. We also show how a single linear programming package can implement these logics computationally if one ''plugs in'' a different column generation subroutine for each logic, although the practicality of this approach has been demonstrated so far only for probabilistic logic.
Keyword:
linear programming
logic
uncertainty
期刊
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6.8
论文数:
3.8K
被引数:
1.5W
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