Supplemental material to "Solving Quantified Modal Logic Problems by Translation to Classical Logics"
<p>These files are associated with the manuscript entitled<br>"Solving Quantified Modal Logic Problems by Translation to Classical Logics"<br>by Alexander Steen, Geoff Sutcliffe, Christoph Benzmüller.</p> <p>Contact: Alexander Steen <alexander.steen@uni-greifswald.de></p> <p>Contents<br>-----------</p> <p> - QMLTP-monomodal-NX0.tar.gz<br> This archive contains the TPTP NX0 representations of the 580 mono-modal<br> problems translated from the QMLTP library [1,2].<br> <br> - QMLTP-monomodal-TF0-embedded-rigid-local.tar.gz<br> This archive contains the embedded TF0 files created <br> from the monomodal NX0 files using the Logic Embedding Tool [3].<br> <br> - QMLTP-monomodal-TH0-embedded-rigid-local.tar.gz<br> This archive contains the embedded TH0 files created <br> from the monomodal NX0 files using the Logic Embedding Tool [3,4].<br> <br> - QMLTP-multimodal-NX0-and-embedded.tar.gz<br> This archive contains the TPTP NX0 representations of the 20 multi-modal<br> problems translated from the QMLTP library [1,2]. Additionally, it<br> contains the 20 embedded TF0 and the 20 embedded THF files created <br> from the NX0 files using the Logic Embedding Tool [3,4].<br> <br> - QMLTP-primary-evaluation-results-QMLTP.zip<br> This archive contains the primary evaluation data creating from<br> running E 3.0.03, Leo-III 1.7.8, Nitpick 2016, Vampire 4.8, <br> MleanCoP 1.3, nanoCoP-M 2.0 on the problem files.<br> All reasoning systems except Nitpick were run on the StarExec Miami cluster with a 60s<br> wall clock and 480 CPU time limit. The StarExec Miami computers have an<br> octa-core Intel Xeon E5-2667 3.20 GHz CPU, 128 GiB memory, and run the<br> CentOS Linux release 7.4.1708 operating system. Nitpick was run on a server<br> with a 60s wall clock time limit. The server has an octa-core Intel Xeon E5-<br> 2609 2.50 GHz CPU, 64 GiB memory, and the CentOS Linux release 7.9.2009<br> operating system.<br> <br> - README<br> This file.<br> <br> <br> <br>[1] T. Raths and J. Otten. The QMLTP Problem Library for First-Order Modal Logics.<br> In B. Gramlich, D. Miller, and U. Sattler, editors, Proceedings of the 6th International Joint Conference on Automated Reasoning,<br> number 7364 in Lecture Notes in Artificial Intelligence, pages 454–461. Springer, 2012.<br>[2] http://www.iltp.de/qmltp/<br>[3] A. Steen. An extensible logic embedding tool for lightweight non-classical reasoning (short paper).<br> In B. Konev, C. Schon, and A. Steen, editors, Proceedings of the 8th Workshop on Practical Aspects of Automated<br> Reasoning, number 3201 in CEUR Workshop Proceedings, 2022.<br>[4] https://github.com/leoprover/logic-embedding</p>
ShareScore
40/100
Overall dataset sharing score
Score breakdown
These five areas show where the dataset supports — or may limit — practical reuse.
- Stewardship
- 8
- Harmonization
- 4
- Access
- 16
- Reuse readiness
- 8
- Engagement
- 4