A new research paper explores dynamic welfare-maximizing pooled testing strategies under budget constraints. The study introduces a theoretical framework where agents have varying utilities and prior probabilities of being healthy, with welfare gained upon certification. The findings suggest that optimal dynamic policies can achieve at most twice the welfare of static allocations, and in some cases, adaptivity offers no benefit. The paper also details approximation algorithms and presents an exact study comparing dynamic and static benchmarks. AI
RANK_REASON The cluster contains a single arXiv paper detailing a new theoretical framework and algorithms for pooled testing. [lever_c_demoted from research: ic=1 ai=0.4]
- alphaXiv
- arXiv
- CatalyzeX Code Finder for Papers
- DagsHub
- Exact-Joint Greedy
- Finster et al.
- Francisco Javier Marmolejo-Cossío
- Gotit.pub
- Greedy
- Hugging Face
- ScienceCast
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