Logic programs with classical negation
Logic programming
Strongly equivalent logic programs
ACM Transactions on Computational Logic (TOCL) - Special issue devoted to Robert A. Kowalski
Extending and implementing the stable model semantics
Artificial Intelligence
Knowledge Representation, Reasoning, and Declarative Problem Solving
Knowledge Representation, Reasoning, and Declarative Problem Solving
Updating Extended Logic Programs through Abduction
LPNMR '99 Proceedings of the 5th International Conference on Logic Programming and Nonmonotonic Reasoning
A consistency-based approach for belief change
Artificial Intelligence
On properties of update sequences based on causal rejection
Theory and Practice of Logic Programming
The DLV system for knowledge representation and reasoning
ACM Transactions on Computational Logic (TOCL)
Towards generalized rule-based updates
IJCAI'97 Proceedings of the 15th international joint conference on Artifical intelligence - Volume 1
Conflict-driven answer set solving
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Iterated theory base change: a computational model
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Back and forth between rules and SE-models
LPNMR'11 Proceedings of the 11th international conference on Logic programming and nonmonotonic reasoning
Rule revision in normal DL logic programs
RR'13 Proceedings of the 7th international conference on Web Reasoning and Rule Systems
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An approach to the revision of logic programs under the answer set semantics is presented. For programs P and Q, the goal is to determine the answer sets that correspond to the revision of P by Q, denoted P * Q. A fundamental principle of classical (AGM) revision, and the one that guides the approach here, is the success postulate. In AGM revision, this stipulates that α ∈ K * α. By analogy with the success postulate, for programs P and Q, this means that the answer sets of Q will in some sense be contained in those of P * Q. The essential idea is that for P * Q, a three-valued answer set for Q, consisting of positive and negative literals, is first determined. The positive literals constitute a regular answer set, while the negated literals make up a minimal set of naf literals required to produce the answer set from Q. These literals are propagated to the program P, along with those rules of Q that are not decided by these literals. The approach differs from work in update logic programs in two main respects. First, we ensure that the revising logic program has higher priority, and so we satisfy the success postulate; second, for the preference implicit in a revision P * Q, the program Q as a whole takes precedence over P, unlike update logic programs, since answer sets of Q are propagated to P. We show that a core group of the AGM postulates are satisfied, as are the postulates that have been proposed for update logic programs.