Foundations of logic programming; (2nd extended ed.)
Foundations of logic programming; (2nd extended ed.)
Prioritized conflict handing for logic programs
ILPS '97 Proceedings of the 1997 international symposium on Logic programming
Preferred answer sets for extended logic programs
Artificial Intelligence
Prioritized logic programming and its application to commonsense reasoning
Artificial Intelligence
Extending and implementing the stable model semantics
Artificial Intelligence
Reasoning with Prioritized Defaults
LPKR '97 Selected papers from the Third International Workshop on Logic Programming and Knowledge Representation
NoMoRe: Non-monotonic Reasoning with Logic Programs
JELIA '02 Proceedings of the European Conference on Logics in Artificial Intelligence
Computing preferred answer sets by meta-interpretation in Answer Set Programming
Theory and Practice of Logic Programming
A semantic framework for preference handling in answer set programming
Theory and Practice of Logic Programming
A framework for compiling preferences in logic programs
Theory and Practice of Logic Programming
Two results for prioritized logic programming
Theory and Practice of Logic Programming
Well-founded semantics for extended logic programs with dynamic preferences
Journal of Artificial Intelligence Research
Graph theoretical characterization and computation of answer sets
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 1
Graphs and colorings for answer set programming
Theory and Practice of Logic Programming
nomore: a system for computing preferred answer sets
LPNMR'05 Proceedings of the 8th international conference on Logic Programming and Nonmonotonic Reasoning
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The integration of preferences into answer set programming constitutes an important practical device for distinguishing certain preferred answer sets from non-preferred ones. To this end, we elaborate upon rule dependency graphs and their colorings for characterizing different preference handling strategies found in the literature. We start from a characterization of (three types of) preferred answer sets in terms of totally colored dependency graphs. In particular, we demonstrate that this approach allows us to capture all three approaches to preferences in a uniform setting by means of the concept of a height function. In turn, we exemplarily develop an operational characterization of preferred answer sets in terms of operators on partial colorings for one particular strategy. In analogy to the notion of a derivation in proof theory, our operational characterization is expressed as a (non-deterministically formed) sequence of colorings, gradually turning an uncolored graph into a totally colored one.