SOURCE-LINKED INTELLIGENCE
Social Laws for Multi-agent Coordination in Stochastic Environments
In multi-agent environments, coordinating agents to prevent interference and ensure robust individual performance is a critical challenge. Previous research on social laws for multi-agent systems has primarily focused on deterministic, goal-based settings. This paper extends the concept of social laws to stochastic, reward-based environments, proposing a formalism for defining and verifying their robustness under various conditions. We introduce the notion of $α$-robustness, a measure of the guaranteed utility each agent retains while pursuing its optimal single agent policy, assuming all agen
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-16T17:05:03.000Z
- arXiv · Artificial Intelligence · 2026-09-16T17:05:03.000Z
First collected: 2026-09-19T20:26:32.566Z. This is not the publication date.