Finite Groundings for ASP with Functions: A Journey through Consistency
Authors: Lukas Gerlach, David Carral, Markus Hecher
IJCAI 2024 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We show reductions that give an intuition for the high level of undecidability. These insights allow for a more fine-grained analysis where we characterize ASP programs as frugal and non-proliferous . For such programs, we are not only able to semi-decide consistency but we also propose a grounding procedure that yields finite groundings on more ASP programs with the concept of forbidden facts. |
| Researcher Affiliation | Academia | Lukas Gerlach1 , David Carral2 , Markus Hecher3 1Knowledge-Based Systems Group, TU Dresden, Dresden, Germany 2LIRMM, Inria, University of Montpellier, CNRS, Montpellier, France 3Massachusetts Institute of Technology, United States lukas.gerlach@tu-dresden.de, david.carral@inria.fr, hecher@mit.edu |
| Pseudocode | Yes | Algorithm 1 Is Forbidden |
| Open Source Code | No | The paper discusses concepts related to open-source tools (like clasp or wasp) but does not provide a link or statement for the source code of the methodology described in this paper. |
| Open Datasets | No | The paper is theoretical and does not conduct experiments on datasets, thus no information about public datasets for training is provided. |
| Dataset Splits | No | The paper is theoretical and does not conduct experiments with dataset splits. Thus, no training/validation/test splits are mentioned. |
| Hardware Specification | No | The paper does not mention any specific hardware used for computations or experiments, as it focuses on theoretical contributions. |
| Software Dependencies | No | The paper mentions various ASP solvers (e.g., clasp, wasp, Alpha, DLV) as context for related work and for illustrative examples, but it does not specify software dependencies with version numbers for the authors' own conceptual work or algorithms. |
| Experiment Setup | No | The paper is theoretical and does not conduct empirical experiments with a specific setup (e.g., hyperparameters, training configurations). Thus, no experimental setup details are provided. |