Automatic Generation of Flexible Plans via Diverse Temporal Planning
Authors: Yotam Amitai, Ayal Taitler, Erez Karpas6049-6057
AAAI 2021 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Finally, an empirical evaluation on a set of IPC benchmarks shows that our approach scales well, and generates TPNs which can generalize the set of plans they are generated from. |
| Researcher Affiliation | Academia | Yotam Amitai, Ayal Taitler, Erez Karpas Technion Israel Institute of Technology yotama@campus.technion.ac.il, {ataitler, karpase}@technion.ac.il |
| Pseudocode | No | The paper describes procedures narratively and with figures, but does not include any clearly labeled pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not provide a statement or link indicating that the source code for the described methodology is publicly available. |
| Open Datasets | Yes | We evaluated our approach on domains from the temporal track IPC in 2011, 2014, and 2018. |
| Dataset Splits | No | The paper uses IPC benchmarks but does not specify how the dataset was split into training, validation, or test sets, nor does it provide percentages or sample counts for these splits. |
| Hardware Specification | Yes | The experiments were performed on Intel i7-7700K 32GB RAM |
| Software Dependencies | Yes | We then construct a COP based on M in Minizinc (Nethercote et al. 2007) and use Gecode (Schulte, Tack, and Lagerkvist 2019) to solve it. ... The Fast Downward planning system (Helmert 2006) extended with the support for structural symmetries and the orbit space search algorithm (Domshlak, Katz, and Shleyfman 2015) with LM-cut heuristic (Helmert and Domshlak 2009) as was used in (Katz et al. 2018). |
| Experiment Setup | Yes | We evaluated all combinations of k chosen from {2, 4, 8}, both compatibility methods (Full & Semi denoted as F,S) and merging transitivity (Strict & Loose denoted as St,L). Thus, for each planning problem, we ran the diverse planner 3 times (for the different values of k), and then ran 4 different versions of our COP (for the different compatibility and transitivity). The experiments were performed on Intel i7-7700K 32GB RAM, with a time limit of 30min for generating the diverse solutions and 30min for the COP task. |