Second MOASEI Competition at AAMAS'2026: A Technical Report
The paper describes the 2026 MOASEI Competition, which evaluates multi-agent decision-making under open-system conditions in wildfire fighting, cybersecurity, and ride-sharing domains.
Evaluation of multi-agent decision-making systems under open-system conditions with varying agent equipment states
Keywords
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Applications
- →Wildfire fighting
- →Cybersecurity
- →Ride-sharing
To understand this paper, make sure you know these concepts first:
- Understanding of multi-agent decision-making systemsfind papers →
- Open-system conditionsfind papers →
Abstract
More Like ThisWe describe the 2026 Methods for Open Agent Systems Evaluation Initiative (MOASEI) Competition, a benchmark event for evaluating multi-agent decision-making under open-system conditions. Building on the inaugural 2025 competition, the 2026 edition retained wildfire fighting, cybersecurity, and ride-sharing domains while adding a bonus wildfire track with frame openness, in which agent equipment states such as suppressant capacities and firefighting range vary over time. The competition also expanded its reporting metrics to emphasize total task completions, mean task-completion time, and mean value of completed tasks. Participation in 2026 was limited: eight teams registered, but only one team submitted a final entry, and that entry targeted the ride-sharing track. The submitted DLC approach used planning and replanning to solve routing problems across agents as passengers appeared. This report summarizes the 2026 competition design, highlights differences from the previous year, and reports ride-sharing evaluation results against baseline policies. DLC is recognized as the 2026 ride-sharing track winner among submitted teams.