Resource allocation with cooperative agents
We study the problem of cooperative resource allocation in multi-agent systems, focusing on scenarios such as hospital networks. In our model, agents (e.g., hospitals) redistribute limited resources, such as medical personnel, in a way that satisfies both local constraints and global equity objectives. We devise ad-hoc optimization strategies for a static scenario, where resource needs are fixed over time. We empirically evaluate the proposed approaches through a set of experiments. Our results demonstrate that our approaches are highly effective.
Authors
- S. Costantini
- F. Gullo
- G. De Gasperis
- P. De Meo
- Alessandro Provetti
Publication Details
- Journal
- BIROn (Birkbeck, University of London)
- Published
- 2025-12-03
- Primary Topic
- Reinforcement Learning in Robotics
- Type
- article
- Field-Weighted Citation Impact
- 0.00