Optimal Multi-Agent Pathfinding Algorithms
Authors: Guni Sharon
AAAI 2015 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | CBS has a major drawback when solving MAPF instances that is dense with agents that conflict frequently. |
| Researcher Affiliation | Academia | Thesis Summary: Optimal Multi-Agent Pathfinding Algorithms Guni Sharon |
| Pseudocode | No | The paper describes algorithms verbally and lists components, but does not include structured pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not provide any statement or link regarding the availability of open-source code for the described methodology. |
| Open Datasets | No | The paper discusses the problem and algorithms but does not provide concrete access information (link, DOI, citation) for any publicly available or open dataset used for training. |
| Dataset Splits | No | The paper does not specify exact dataset split percentages, sample counts, or refer to predefined splits needed for reproduction. |
| Hardware Specification | No | The paper does not provide any specific details about the hardware used for experiments. |
| Software Dependencies | No | The paper does not provide specific software dependencies with version numbers (e.g., library or solver names with version numbers). |
| Experiment Setup | No | The paper does not provide specific experimental setup details such as hyperparameter values, training configurations, or system-level settings. |