Time-Independent Planning for Multiple Moving Agents
Authors: Keisuke Okumura, Yasumasa Tamura, Xavier Défago11299-11307
AAAI 2021 | Conference PDF | Archive PDF | Plain Text | 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 {okumura.k, tamura, defago}@coord.c.titech.ac.jp |
| 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. |