Sketched Answer Set Programming
Sketched Answer Set Programming
Answer Set Programming (ASP) is a powerful modeling formalism for combinatorial problems. However, writing ASP models is not trivial. We propose a novel method, called Sketched Answer Set Programming (SkASP), aiming at supporting the user in resolving this issue. The user writes an ASP program while marking uncertain parts open with question marks. In addition, the user provides a number of positive and negative examples of the desired program behaviour. The sketched model is rewritten into another ASP program, which is solved by traditional methods. As a result, the user obtains a functional and reusable ASP program modelling her problem. We evaluate our approach on 21 well known puzzles and combinatorial problems inspired by Karp's 21 NP-complete problems and demonstrate a use-case for a database application based on ASP.
15 pages, 11 figures; to appear in ICTAI 2018
- French National Centre for Scientific Research France
- Université Catholique de Louvain Belgium
- University of Montpellier France
- Katholieke Universiteit Leuven Belgium
- KU Leuven Belgium
FOS: Computer and information sciences, Technology, constraint programming, Sketching, Science & Technology, COMPLEXITY, relational learning, Computer Science - Artificial Intelligence, Constraint learning, Answer set programming, inductive logic programming, Inductive logic programming, [INFO] Computer Science [cs], Computer Science, Artificial Intelligence, Relational learning, constraint learning, Artificial Intelligence (cs.AI), Computer Science, sketching, Constraint programming, answer set programming
FOS: Computer and information sciences, Technology, constraint programming, Sketching, Science & Technology, COMPLEXITY, relational learning, Computer Science - Artificial Intelligence, Constraint learning, Answer set programming, inductive logic programming, Inductive logic programming, [INFO] Computer Science [cs], Computer Science, Artificial Intelligence, Relational learning, constraint learning, Artificial Intelligence (cs.AI), Computer Science, sketching, Constraint programming, answer set programming
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