Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in Coakley et alK. L. Coakley, T. Snelleman, H. Hoos, and O. E. Gundersen, "The embrace of open science: An analysis of a decade of AI research and 56 800 conference papers," Under Review, 2026..
Time-Independent Planning for Multiple Moving Agents
Authors: Keisuke Okumura, Yasumasa Tamura, Xavier Défago11299-11307
AAAI 2021 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Empirical results in a simulated environment with stochastic delays of agents moves support the validity of our proposal. |
| Researcher Affiliation | Academia | Keisuke Okumura, Yasumasa Tamura, Xavier D efago School of Computing, Tokyo Institute of Technology Tokyo, Japan EMAIL |
| Pseudocode | Yes | Algorithm 1 Causal-PIBT Algorithm 2 Procedures of Causal-PIBT |
| Open Source Code | Yes | The simulator was developed in C++ 1, and all experiments were run on a laptop with Intel Core i9 2.3GHz CPU and 16GB RAM. 1https://github.com/Kei18/time-independent-planning |
| Open Datasets | Yes | We used the MAPF-DP problem... one scenario from MAPF benchmarks (Stern et al. 2019)... large fields from the MAPF benchmarks. |
| Dataset Splits | No | The paper does not provide specific percentages or counts for training, validation, or test splits. It mentions using "100 repetitions" for trials but no explicit data partitioning. |
| Hardware Specification | Yes | The simulator was developed in C++ 1, and all experiments were run on a laptop with Intel Core i9 2.3GHz CPU and 16GB RAM. |
| Software Dependencies | No | The paper mentions that "The simulator was developed in C++" but does not specify versions for the C++ compiler or any libraries/dependencies used. |
| Experiment Setup | Yes | The delay probabilities pi were chosen uniformly at random from [0, p]... an adapted version of Enhanced CBS (ECBS) (Barer et al. 2014), bounded suboptimal MAPF solver, was used to obtain valid MAPF-DP plans, where the suboptimality was 1.1. |