Graphs and colorings for answer set programming

Computer Science – Artificial Intelligence

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

Scientific paper

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 in 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. (To appear in Theory and Practice of Logic Programming (TPLP))

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

Graphs and colorings for answer set programming does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Graphs and colorings for answer set programming, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Graphs and colorings for answer set programming will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-197467

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.