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]
On the Impact of Modal Depth in Epistemic Planning
Authors: Tristan Charrier, Bastien Maubert, Francçois Schwarzentruber
IJCAI 2016 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | First, we prove that the epistemic planning problem with propositional preconditions and without postconditions is in PSPACE, and is thus PSPACE-complete. Second, we prove that very simple epistemic preconditions are enough to make the epistemic planning problem undecidable: preconditions of modal depth at most two suffice. |
| Researcher Affiliation | Academia | Tristan Charrier Universit e de Rennes 1 IRISA EMAIL Bastien Maubert Universit a degli studi di Napoli Federico II EMAIL Franc ois Schwarzentruber ENS Rennes / IRISA EMAIL |
| Pseudocode | Yes | Figure 2: Algorithm mc for model checking LitC0 |
| Open Source Code | No | No statement is made regarding the release of open-source code for the described methodology, nor are any links provided. |
| Open Datasets | No | The paper is theoretical and does not involve the use of datasets for training or evaluation. |
| Dataset Splits | No | The paper is theoretical and does not involve data partitioning into training, validation, or test sets. |
| Hardware Specification | No | The paper is purely theoretical and does not mention any specific hardware used for experiments. |
| Software Dependencies | No | The paper is theoretical and does not provide specific software dependencies or version numbers. |
| Experiment Setup | No | The paper is theoretical and does not include details on experimental setup, hyperparameters, or system-level training settings. |