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arXiv · 2606.01309

Multiagent Matroid Upgrading: Greedy is Fair and Efficient

Qingwen Ma·Chao Peng·Changfeng Xu·Chenyang Xu·Ruilong Zhang
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Abstract

This paper introduces a general multiagent matroid upgrading problem that models a broad class of real-world resource allocation tasks. In this setting, there are multiple agents and a ground set of elements, where each element is assigned to a specific agent and has two associated costs: a default cost and a reduced (upgraded) cost. Upgrading an element lowers its cost to the upgraded value, while non-upgraded elements retain their default costs. Each agent is associated with its own matroid, with the goal of finding a minimum-cost basis. The central task is to select at most k elements to upgrade so as to minimize a non-decreasing convex function over the agents' minimum basis costs, capturing both efficiency and fairness objectives in multiagent systems.

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Qingwen Ma, Chao Peng, Changfeng Xu, Chenyang Xu, Ruilong Zhang. 2026-05-31. Multiagent Matroid Upgrading: Greedy is Fair and Efficient. https://arxiv.org/abs/2606.01309

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