Variable-Deletion Backdoors to Planning
Authors: Martin Kronegger, Sebastian Ordyniak, Andreas Pfandler
AAAI 2015 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | In this work we improve the situation by defining a new type of variabledeletion backdoors based on the extended causal graph of a planning instance. For this notion of backdoors several fixed-parameter tractable algorithms are identified. Furthermore, we explore the capabilities of polynomial time preprocessing, i.e., we check whether there exists a polynomial kernel. Our results also show the close connection between planning and verification problems such as Vector Addition System with States (VASS). |
| Researcher Affiliation | Academia | 1Vienna University of Technology, Vienna, Austria 2Masaryk University, Brno, Czech Republic 3University of Siegen, Siegen, Germany |
| Pseudocode | No | The paper describes procedures and constructions (e.g., for VASS) in text, but it does not include any clearly labeled pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not provide any statements or links indicating the availability of open-source code for the methodology described. |
| Open Datasets | No | This is a theoretical paper focused on algorithms and complexity analysis. It does not use or reference any datasets for training. |
| Dataset Splits | No | This is a theoretical paper and does not involve experimental validation or dataset splits. |
| Hardware Specification | No | This is a theoretical paper and does not mention any specific hardware used for running experiments. |
| Software Dependencies | No | This is a theoretical paper. No specific software dependencies with version numbers are mentioned that would be needed to replicate experimental results or implementations. |
| Experiment Setup | No | This is a theoretical paper. There are no experimental setup details, hyperparameters, or system-level training settings described. |