Robust Multiagent Collaboration Through Weighted Max-Min T-Joins

Many multiagent tasks---such as fair resource allocation, partnerships between cities, exchanges between schools, and reviewer assignment---require selecting a group of agents such that collaboration remains effective even in the worst case. The weighted max--min T-join problem formalizes this challenge by seeking a subset of vertices whose minimum-weight matching is maximized, thereby ensuring robust outcomes against unfavorable pairings.

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