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Emergence World: Adversarial Stress-Testing of Long-Horizon Multi-Agent Systems

The paper introduces Emergence World, a multi-agent environment for adversarial stress testing of long-horizon autonomous systems. It describes experiments with eight parallel worlds of ten agents, showing that even safe models can exhibit unexpected failure modes when interacting in complex, persistent systems.

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PublishedSeptember 15, 2026Deepak Akkil, Tamer Abuelsaad, Karthik Vikram
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WHY IT MAY MATTER

This research highlights the challenges of ensuring safety in persistent, interconnected AI systems through adversarial testing, indicating that model-level alignment alone may not be sufficient for system-wide resilience.

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