When Should Agents Coordinate in Differentiable Sequential Decision Problems?
Fuente:
arXiv
Guardado en:
| Autores principales: | , , , |
|---|---|
| Formato: | Preprint |
| Publicado: |
2026
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
| _version_ | 1866917245691625472 |
|---|---|
| author | Probine, Caleb Low, Su Ann Fridovich-Keil, David Topcu, Ufuk |
| author_facet | Probine, Caleb Low, Su Ann Fridovich-Keil, David Topcu, Ufuk |
| contents | Multi-robot teams must coordinate to operate effectively. When a team operates in an uncoordinated manner, and agents choose actions that are only individually optimal, the team's outcome can suffer. However, in many domains, coordination requires costly communication. We explore the value of coordination in a broad class of differentiable motion-planning problems. In particular, we model coordinated behavior as a spectrum: at one extreme, agents jointly optimize a common team objective, and at the other, agents make unilaterally optimal decisions given their individual decision variables, i.e., they operate at Nash equilibria. We then demonstrate that reasoning about coordination in differentiable motion-planning problems reduces to reasoning about the second-order properties of agents' objectives, and we provide algorithms that use this second-order reasoning to determine at which times a team of agents should coordinate. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2602_03674 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | When Should Agents Coordinate in Differentiable Sequential Decision Problems? Probine, Caleb Low, Su Ann Fridovich-Keil, David Topcu, Ufuk Multiagent Systems Computer Science and Game Theory Robotics Optimization and Control Multi-robot teams must coordinate to operate effectively. When a team operates in an uncoordinated manner, and agents choose actions that are only individually optimal, the team's outcome can suffer. However, in many domains, coordination requires costly communication. We explore the value of coordination in a broad class of differentiable motion-planning problems. In particular, we model coordinated behavior as a spectrum: at one extreme, agents jointly optimize a common team objective, and at the other, agents make unilaterally optimal decisions given their individual decision variables, i.e., they operate at Nash equilibria. We then demonstrate that reasoning about coordination in differentiable motion-planning problems reduces to reasoning about the second-order properties of agents' objectives, and we provide algorithms that use this second-order reasoning to determine at which times a team of agents should coordinate. |
| title | When Should Agents Coordinate in Differentiable Sequential Decision Problems? |
| topic | Multiagent Systems Computer Science and Game Theory Robotics Optimization and Control |
| url | https://arxiv.org/abs/2602.03674 |