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AMAI
2006
Springer

Possibilistic uncertainty handling for answer set programming

9 years 3 months ago
Possibilistic uncertainty handling for answer set programming
In this work, we introduce a new framework able to deal with a reasoning that is at the same time non monotonic and uncertain. In order to take into account a certainty level associated to each piece of knowledge, we use possibility theory to extend the non monotonic semantics of stable models for logic programs with default negation. By means of a possibility distribution we define a clear semantics of such programs by introducing what is a possibilistic stable model. We also propose a syntactic process based on a fix-point operator to compute these particular models representing the deductions of the program and their certainty. Then, we show how
Pascal Nicolas, Laurent Garcia, Igor Stépha
Added 10 Dec 2010
Updated 10 Dec 2010
Type Journal
Year 2006
Where AMAI
Authors Pascal Nicolas, Laurent Garcia, Igor Stéphan, Claire Lefèvre
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