On the Compilability of Bounded Numeric Planning
Authors: Nicola Gigante, Enrico Scala
IJCAI 2023 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | Bounded numeric planning, where each numeric variable domain is bounded, is PSPACE-complete, but such a complexity result does not capture how hard it really is, since the same holds even for the practically much easier STRIPS fragment. A finer way to compare the difficulty of planning formalisms is through the notion of compilability, which has been however extensively studied only for classical planning by Nebel. This paper extends Nebel s framework to the setting of bounded numeric planning. |
| Researcher Affiliation | Academia | Nicola Gigante1 , Enrico Scala2 1Free University of Bozen-Bolzano, Italy 2University of Brescia, Italy |
| Pseudocode | No | The paper does not contain any pseudocode or clearly labeled algorithm blocks. |
| Open Source Code | No | The paper does not provide any concrete access to source code for the methodology described. |
| Open Datasets | No | This is a theoretical paper and does not conduct experiments involving datasets. |
| Dataset Splits | No | This is a theoretical paper and does not involve training, validation, or test dataset splits. |
| Hardware Specification | No | This is a theoretical paper and does not describe any specific hardware used for experiments. |
| Software Dependencies | No | This is a theoretical paper and does not list any specific software dependencies with version numbers for experimental setup. |
| Experiment Setup | No | This is a theoretical paper and does not provide details about an experimental setup, hyperparameters, or training configurations. |