Disjunctive stable models: unfounded sets, fixpoint semantics, and computation
Information and Computation
Enhancing disjunctive logic programming systems by SAT checkers
Artificial Intelligence
Equilibria in heterogeneous nonmonotonic multi-context systems
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
A uniform integration of higher-order reasoning and external evaluations in answer-set programming
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Semantics and complexity of recursive aggregates in answer set programming
Artificial Intelligence
Pushing efficient evaluation of HEX programs by modular decomposition
LPNMR'11 Proceedings of the 11th international conference on Logic programming and nonmonotonic reasoning
Answer set programming at a glance
Communications of the ACM
Unfounded sets for disjunctive logic programs with arbitrary aggregates
LPNMR'05 Proceedings of the 8th international conference on Logic Programming and Nonmonotonic Reasoning
Effective integration of declarative rules with external evaluations for semantic-web reasoning
ESWC'06 Proceedings of the 3rd European conference on The Semantic Web: research and applications
Conflict-driven answer set solving: From theory to practice
Artificial Intelligence
Conflict-driven asp solving with external sources
Theory and Practice of Logic Programming
Eliminating nonmonotonic DL-Atoms in description logic programs
RR'13 Proceedings of the 7th international conference on Web Reasoning and Rule Systems
Data repair of inconsistent DL-programs
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
| Hi-index | 0.00 |
HEX programs extend logic programs with external computations through external atoms, whose answer sets are the minimal models of the Faber-Leone-Pfeifer-reduct. As already reasoning from Horn programs with nonmonotonic external atoms of polynomial complexity is on the second level of the polynomial hierarchy, answer set checking needs special attention; simply computing reducts and searching for smaller models does not scale well. We thus extend an approach based on unfounded sets to HEX and integrate it in a Conflict Driven Clause Learning framework for HEX program evaluation. It reduces the check to a search for unfounded sets, which is more efficiently implemented as a SAT problem. We give a basic encoding for HEX and show optimizations by additional clauses. Experiments show that the new approach significantly decreases runtime.