Planning with Explanations for Finding Desired Meeting Points on Graphs
Authors: Keisuke Otaki10319-10326
AAAI 2022 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We experimentally demonstrate that our search-based framework is promising to solve instances with generating explanations in a sequential decision-making process. |
| Researcher Affiliation | Industry | Keisuke Otaki Toyota Central R&D Labs., Inc. otaki@mosk.tytlabs.co.jp |
| Pseudocode | Yes | Algorithm 1: Generate-and-test when G is fixed |
| Open Source Code | No | The paper mentions "All scripts are written in Julia 1.6." but does not provide a specific repository link, explicit code release statement, or code in supplementary materials for the methodology described in this paper. |
| Open Datasets | No | To generate random instances, we select up to k 12 customers on V randomly." The paper describes using "randomly generated road networks" and "extract a network from Kyoto, Japan from Openstreetmap", but does not provide concrete access information (link, DOI, repository name, or formal citation with authors/year) for these specific datasets as used in their experiments. |
| Dataset Splits | No | The paper does not provide specific dataset split information (exact percentages, sample counts, citations to predefined splits, or detailed splitting methodology) needed to reproduce the data partitioning. |
| Hardware Specification | Yes | All evaluations are conducted on a machine (Ubuntu 20.04) with an Intel Core i5-6260U CPU at 1.80GHz and 32GB memory. |
| Software Dependencies | Yes | All scripts are written in Julia 1.6. |
| Experiment Setup | Yes | For Alg. 1, we set k = 5 (N = 20) and k = 3 (N = 40, 60)." and "We simplify two costs as fresidents(u, v) := d(u, v)/α and froad(u, v) := d(u, v)/β with α = β = 2. |