arXiv Artificial Intelligence

Credit Fairness: Online Fairness In Shared Resource Pools

Credit Fairness: Online Fairness In Shared Resource Pools

Quick summary

arXiv:2601.17944v2 Announce Type: replace-cross Abstract: We study repeated allocation of shared resources among agents with time-varying demands and capped linear utilities. In this setting, independently maximizing the minimum endowment-normalized utility in each round satisfies sharing incentives (agents weakly prefer participating in the mechanism to not participating), strategyproofness (agents have no incentive to misreport their demands), and Pareto efficiency. However, this max-min mechanism can lead to large disparities in the total resources received by agents, even when they have th

Key takeaways

  • arXiv:2601.17944v2 Announce Type: replace-cross Abstract: We study repeated allocation of shared resources among agents with time-varying demands and capped linear utilities.
  • In this setting, independently maximizing the minimum endowment-normalized utility in each round satisfies sharing incentives (agents weakly prefer participating in the mechanism to not participating), strategyproofness (agents have no incentive to misreport their demands), and Pareto efficiency.
  • However, this max-min mechanism can lead to large disparities in the total resources received by agents, even when they have th

Why it matters

The value of this work lies as much in how it was tested as in the claim itself. Sample design, baselines, uncertainty and replication help separate a laboratory result from real-world impact.

Kaynak sitede devamını oku: arXiv Artificial Intelligence ↗