Conflict-driven ASP Solving with External Sources and Program Splits

Authors: Christoph Redl

IJCAI 2017 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Experimental In Section 6 we present our implementation and experimental results, which show a significant in some cases even exponential speedup.
Researcher Affiliation Academia Institut f ur Informationssysteme, Technische Universit at Wien Favoritenstraße 9-11, A-1040 Vienna, Austria redl@kr.tuwien.ac.at
Pseudocode Yes Algorithm 1: HEX-CDNL; Algorithm 2: Inconsistency Analysis
Open Source Code No The paper mentions integrating techniques into DLVHEX (http:/www.kr.tuwien.ac.at/research/systems/dlvhex) and provides a link to benchmark encodings (https:/github.com/hexhex/core/tree/master/benchmarks), but does not provide a direct link or explicit statement for the source code of the specific methodology described in the paper.
Open Datasets No For the experiment we consider for each size n ten randomly generated instances with n domain elements, n 5 + 1 properties, a random function m, and a random number of constraints, such that their count has an expected value of n.
Dataset Splits No The paper does not provide specific training/validation/test dataset splits or describe a cross-validation setup.
Hardware Specification Yes All benchmarks were run on a Linux machine with two 12-core AMD Opteron 6176 SE CPUs and 128 GB RAM; timeout was 300 secs and memout 8 GB per instance.
Software Dependencies Yes For the experiments, we integrated our techniques into the reasoner DLVHEX4 with GRINGO 4.5.4 and CLASP 3.1.4 as backends.
Experiment Setup Yes All benchmarks were run on a Linux machine with two 12-core AMD Opteron 6176 SE CPUs and 128 GB RAM; timeout was 300 secs and memout 8 GB per instance. We used the HTCondor load distribution system (http:/research.cs. wisc.edu/htcondor) to ensure robust runtimes (i.e., deviations of runs on the same instance are negligible).