Name
Abstract | ||
|---|---|---|
Multi-agent path finding (MAPF) is well-studied in artificial intelligence, robotics, theoretical computer science and operations research. We discuss issues that arise when generalizing MAPF methods to real-world scenarios and four research directions that address them. We emphasize the importance of addressing these issues as opposed to developing faster methods for the standard formulation of the MAPF problem. |
Year | Venue | Field |
|---|---|---|
2017 | arXiv: Artificial Intelligence | Data science,Generalization,Computer science,Artificial intelligence,Machine learning,Robotics |
DocType | Volume | Citations |
Journal | abs/1702.05515 | 6 |
PageRank | References | Authors |
0.45 | 12 | 10 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hang Ma | 1 | 85 | 12.86 |
| Sven Koenig | 2 | 3125 | 361.22 |
| Nora Ayanian | 3 | 123 | 16.66 |
| Liron Cohen | 4 | 36 | 11.24 |
| Wolfgang Hönig | 5 | 53 | 7.90 |
| T. K. Satish Kumar | 6 | 23 | 5.71 |
| Tansel Uras | 7 | 156 | 14.15 |
| Hong Xu | 8 | 110 | 19.19 |
| Craig A. Tovey | 9 | 716 | 68.57 |
| Guni Sharon | 10 | 194 | 19.32 |