Structurally Restricted Fragments of Numeric Planning – a Complexity Analysis
Authors: Alexander Shleyfman, Daniel Gnad, Peter Jonsson
AAAI 2023 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | First, we show that plan existence for tasks where all numeric variables are root nodes in the causal graph is in PSPACE. Second, we show that for tasks with only numeric leaf variables the problem is decidable, and that it is in PSPACE if the propositional state space has a fixed size. We focus completely on providing decidability results in this paper and leave hardness results for future work. |
| Researcher Affiliation | Academia | 1The Department of Computer Science, Bar-Ilan University, Ramat Gan, Israel 2Department of Computer and Information Science, Link oping University, Link oping, Sweden |
| Pseudocode | No | The paper does not contain structured pseudocode or clearly labeled algorithm blocks. |
| Open Source Code | No | The paper does not provide an explicit statement about releasing its source code or a link to a code repository for the described methodology. |
| Open Datasets | No | The paper does not mention the use of any specific datasets, nor does it provide concrete access information for a publicly available or open dataset. |
| Dataset Splits | No | The paper does not provide specific dataset split information (e.g., percentages, sample counts, or methodology for training, validation, and test sets). |
| Hardware Specification | No | The paper does not provide specific hardware details used for running experiments. |
| Software Dependencies | No | The paper does not provide specific ancillary software details with version numbers (e.g., library or solver names). |
| Experiment Setup | No | The paper focuses on theoretical analysis and proofs, and therefore does not include details about an experimental setup, such as hyperparameters or training configurations. |