Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in [1]
Backdoors to Planning
Authors: Martin Kronegger, Sebastian Ordyniak, Andreas Pfandler
AAAI 2014 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | In this work, we introduce two notions of backdoors building upon the causal graph. We analyze the complexity of ο¬nding a small backdoor (detection) and using the backdoor to solve the problem (evaluation) in the light of planning with (un)bounded plan length/domain of the variables. For each setting we present either an fpt-result or rule out the existence thereof by showing parameterized intractability. |
| Researcher Affiliation | Academia | Martin Kronegger Vienna University of Technology, Vienna, Austria EMAIL Sebastian Ordyniak Masaryk University, Brno, Czech Republic EMAIL Andreas Pfandler Vienna University of Technology, Vienna, Austria EMAIL |
| Pseudocode | No | The paper describes algorithms and proofs in narrative text but does not include any clearly labeled pseudocode blocks or algorithm figures. |
| Open Source Code | No | The paper does not provide any links to open-source code for the described methodology or state that code is available. |
| Open Datasets | No | The paper is theoretical and does not involve experiments with datasets. |
| Dataset Splits | No | The paper is theoretical and does not involve empirical experiments requiring dataset splits. |
| Hardware Specification | No | The paper focuses on theoretical complexity analysis and does not mention any specific hardware used for experiments. |
| Software Dependencies | No | The paper is theoretical and does not list any specific software dependencies with version numbers. |
| Experiment Setup | No | The paper is theoretical and does not describe any experimental setup details such as hyperparameters or training configurations. |