## Institut für Informatik und Computational Science

More on nomore
(2002)

More on nomore
(2002)

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

We investigate the usage of rule dependency graphs and their colorings for characterizing and computing answer sets of logic programs. This approach provides us with insights into the interplay between rules when inducing answer sets. We start with different characterizations of answer sets in terms of totally colored dependency graphs that differ ill graph-theoretical aspects. We then develop a series of operational characterizations of answer sets in terms of operators on partial colorings. In analogy to the notion of a derivation in proof theory, our operational characterizations are expressed as (non-deterministically formed) sequences of colorings, turning an uncolored graph into a totally colored one. In this way, we obtain an operational framework in which different combinations of operators result in different formal properties. Among others, we identify the basic strategy employed by the noMoRe system and justify its algorithmic approach. Furthermore, we distinguish operations corresponding to Fitting's operator as well as to well-founded semantics