DMCA
Experiencing ASP with real world applications (2008)
| Venue: | IN: PROCEEDINGS OF THE FIFTEENTH RCRA WORKSHOP ON EXPERIMENTAL EVALUATION OF ALGORITHMS FOR SOLVING PROBLEMS WITH COMBINATORIAL EXPLOSION |
| Citations: | 1 - 0 self |
BibTeX
@INPROCEEDINGS{Terracina08experiencingasp,
author = {G. Terracina and E. De Francesco and C. Panetta and N. Leone},
title = { Experiencing ASP with real world applications},
booktitle = {IN: PROCEEDINGS OF THE FIFTEENTH RCRA WORKSHOP ON EXPERIMENTAL EVALUATION OF ALGORITHMS FOR SOLVING PROBLEMS WITH COMBINATORIAL EXPLOSION},
year = {2008},
publisher = {}
}
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Abstract
Disjunctive logic programming under answer set semantics (DLP, ASP) is a powerful formalism for knowledge representation and reasoning. The language of DLP is very expressive, and allows for modelling complex combinatorial problems. However, despite the high expressiveness of this language, the success of DLP systems is still dimmed when the applications of interest become data intensive (current DLP systems work only in main memory) or they involve some inherently procedural sub-tasks or the handling of complex data structures. The main goal of this paper is precisely to improve efficiency and usability of DLP systems in these contexts, and verify these improvements by a benchmarking activity on real-world applications. We present a DLP system which: (i) carries out as much as possible of the reasoning tasks in mass memory without degrading performances, thus allowing to deal with data-intensive applications; (ii) extends the expressiveness of DLP with external function calls, yet improving efficiency (at least for procedural sub-tasks) and knowledge-modelling power; (iii) extends the expressiveness of DLP for supporting also the management of recursive data structures (lists). We test the system on four main areas: data-integration, combinatorial problems, data transformation, and string similarity computation. The experimental results are very encouraging: the proposed system can handle significantly larger amounts of data than competitor systems, and it is also faster in response time.
Keyphrases
dlp system real world application procedural sub-tasks main memory knowledge-modelling power main area proposed system recursive data structure competitor system complex data structure mass memory current dlp system similarity computation response time combinatorial problem external function data transformation data-intensive application knowledge representation complex combinatorial problem disjunctive logic powerful formalism real-world application main goal benchmarking activity experimental result high expressiveness
