Tight Bounds for HTN Planning with Task Insertion
Authors: Ron Alford, Pascal Bercher, David W. Aha
IJCAI 2015 | Venue PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We lower that bound proving NEXPTIME-completeness and further prove tight complexity bounds along two axes: whether variables are allowed in method and action schemas, and whether methods must be totally ordered. We also introduce a new planning technique called acyclic progression, which we use to define provably efficient TIHTN planning algorithms. |
| Researcher Affiliation | Academia | Ron Alford ASEE/NRL Postdoctoral Fellow Washington, DC, USA EMAIL Pascal Bercher Ulm University Ulm, Germany EMAIL David W. Aha U.S. Naval Research Laboratory Washington, DC, USA EMAIL |
| Pseudocode | No | The paper describes the acyclic progression procedure in text but does not provide it in a structured pseudocode or algorithm block. |
| Open Source Code | No | The paper does not contain any statement about making its source code available or provide a link to a code repository. |
| Open Datasets | No | This is a theoretical paper and does not use or train on datasets. |
| Dataset Splits | No | This is a theoretical paper and does not discuss dataset splits for training, validation, or testing. |
| Hardware Specification | No | This is a theoretical paper and does not mention any hardware specifications used for experiments. |
| Software Dependencies | No | This is a theoretical paper and does not list any specific software dependencies with version numbers. |
| Experiment Setup | No | This is a theoretical paper and does not describe any experimental setup details such as hyperparameters or training configurations. |