Forgetting in Modular Answer Set Programming
Authors: Ricardo Gonçalves, Tomi Janhunen, Matthias Knorr, João Leite, Stefan Woltran2843-2850
AAAI 2019 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | In this paper, we present a novel class of forgetting operators and show that such operators can always be successfully applied in Modular ASP to forget all kinds of atoms input, output and hidden overcoming the impossibility results that exist for general ASP. Additionally, we investigate conditions under which this class of operators preserves the module theorem in Modular ASP, thus ensuring that answer sets of modules can still be composed, and how the module theorem can always be preserved if we further allow the reconfiguration of modules. |
| Researcher Affiliation | Academia | 1Universidade Nova de Lisboa 2Aalto University 3Vienna University of Technology |
| Pseudocode | No | The paper contains formal definitions, theorems, and examples, but no pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not provide any statement about making source code for their methodology publicly available, nor does it provide links to any code repositories. |
| Open Datasets | No | This is a theoretical paper and does not involve datasets for training or experimentation. |
| Dataset Splits | No | This is a theoretical paper and does not involve datasets or data splits for validation. |
| Hardware Specification | No | This is a theoretical paper and does not describe any experimental setup or mention specific hardware used. |
| Software Dependencies | No | This is a theoretical paper and does not describe any experimental setup or mention specific software dependencies with version numbers. |
| Experiment Setup | No | This is a theoretical paper and does not describe an experimental setup with hyperparameters or system-level training settings. |