New Compilation Languages Based on Restricted Weak Decomposability
Authors: Petr Illner
AAAI 2025 | Venue PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Our experiments demonstrate that nw DNNF circuits are suitable for computing MPEs in two-layer Bayesian networks (BNs) with large domains. |
| Researcher Affiliation | Academia | Petr Illner Department of Theoretical Computer Science and Mathematical Logic, Faculty of Mathematics and Physics Charles University, Czech Republic EMAIL |
| Pseudocode | No | We refer the curious reader to (Illner and Kuˇcera 2024) for a more detailed description of Bella and the pseudocode, where the methods compute Components and compute New Cut were changed as described below. |
| Open Source Code | Yes | 1https://github.com/Illner/Bella Compiler |
| Open Datasets | No | We implemented Bels2 to (randomly) generate and convert such BNs into CNF formulae using the encodings mentioned in this paper. |
| Dataset Splits | No | Ten instances were created for each density. Since the compilers are randomised, each instance was compiled three times, and the given results are averages. |
| Hardware Specification | Yes | The experiments3 were performed on a Linux machine (Debian 11) using an AMD EPYC 7543 2.8GHz processor and 512 Gi B of RAM. |
| Software Dependencies | No | The experiments3 were performed on a Linux machine (Debian 11) using an AMD EPYC 7543 2.8GHz processor and 512 Gi B of RAM. The time-out (resp. memory-out) was set to two/six hours (resp. 16 GB). |
| Experiment Setup | Yes | The time-out (resp. memory-out) was set to two/six hours (resp. 16 GB). The following compilers were considered: Bella, D44 (the randomised variant introduced by Illner and Kuˇcera (2024) was used), C2D5, and Sharp SAT-TD6. Ten instances were created for each density. Since the compilers are randomised, each instance was compiled three times, and the given results are averages. |