Computer Science – Artificial Intelligence
Scientific paper
2000-11-21
LPAR 2000, Lecture Notes in Artificial Intelligence, vol. 1955, Springer, 2000, pp. 225-239
Computer Science
Artificial Intelligence
15 pages, 3 eps-figures
Scientific paper
Many logic programming based approaches can be used to describe and solve combinatorial search problems. On the one hand there is constraint logic programming which computes a solution as an answer substitution to a query containing the variables of the constraint satisfaction problem. On the other hand there are systems based on stable model semantics, abductive systems, and first order logic model generators which compute solutions as models of some theory. This paper compares these different approaches from the point of view of knowledge representation (how declarative are the programs) and from the point of view of performance (how good are they at solving typical problems).
Denecker Marc
Mot Emmanuel de
Pelov Nikolay
No associations
LandOfFree
Logic Programming Approaches for Representing and Solving Constraint Satisfaction Problems: A Comparison 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 Logic Programming Approaches for Representing and Solving Constraint Satisfaction Problems: A Comparison, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Logic Programming Approaches for Representing and Solving Constraint Satisfaction Problems: A Comparison will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-176359