How to design fair and strategic facility location mechanisms?
Analyzing Incentives and Fairness in Ordered Weighted Average for Facility Location Games
This paper investigates the use of Ordered Weighted Average (OWA) methods, a common approach in fuzzy systems, as decision-making mechanisms in multi-agent facility location games.
The key finding is that while OWAs offer flexibility, there's a fundamental trade-off between creating a system that is simultaneously resistant to manipulation by individual agents and fair to all participants. This has implications for designing LLM-based multi-agent systems, where balancing strategic behavior and overall fairness is crucial. For instance, if an LLM system uses a voting-like mechanism to make decisions, understanding the fairness and manipulability of different aggregation methods, like OWAs, becomes essential.