Abstract
Possibilistic answer set programming (PASP)
extends answer set programming (ASP) by
attaching to each rule a degree of certainty.
While such an extension is important from
an application point of view, existing semantics
are not well-motivated, and do not always
yield intuitive results. To develop a
more suitable semantics, we first introduce
a characterization of answer sets of classical
ASP programs in terms of possibilistic
logic where an ASP program specifies a set of
constraints on possibility distributions. This
characterization is then naturally generalized
to define answer sets of PASP programs. We
furthermore provide a syntactic counterpart,
leading to a possibilistic generalization of the
well-known Gelfond-Lifschitz reduct, and we
show how our framework can readily be implemented
using standard ASP solvers.
Original language | English |
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Title of host publication | Proceedings of the 26th Conference on Uncertainty in Artificial Intelligence (UAI 2010) |
Editors | Peter Grünwald, Peter Spirtes |
Publisher | AUAI Press |
Number of pages | 8 |
ISBN (Print) | 9780974903965 |
Publication status | Published - 2010 |
Event | The 26th Conference on Uncertainty in Artificial Intelligence (UAI 2010) - Catalina Island, California, United States Duration: 08 Jul 2010 → 11 Jul 2010 |
Conference
Conference | The 26th Conference on Uncertainty in Artificial Intelligence (UAI 2010) |
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Country/Territory | United States |
City | California |
Period | 08/07/2010 → 11/07/2010 |