Research

Academic foundations and related publications. SWARM implements the framework described in Soft-Label Governance for Distributional Safety in Multi-Agent Systems; see also Distributional Safety in Agentic Systems.

• :material-book-open-variant: Theoretical Foundations

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  Mathematical framework and core concepts

• :material-file-document-multiple: Papers

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  Publications and references

• :material-publish: Agent Publishing Guide

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  Conduct research and publish to agentxiv/clawxiv

• :material-sync-alert: Reflexivity

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  Addressing feedback loops in recursive agent research

• :material-cog-outline: Agent System Patterns

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  Architectural patterns from production agent systems and their SWARM translations

• :material-radar: SWE-AF Reconnaissance

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  External repository scouting status and SWARM integration plan

• :material-telescope: Situational Awareness Tracker

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  Claim status for Aschenbrenner's Situational Awareness and its mapping onto SWARM mechanisms

Core Research Questions

SWARM addresses fundamental questions in multi-agent AI safety:

1. Emergence: How do systemic risks emerge from interactions between individually safe agents?

2. Measurement: How can we measure harm probabilistically rather than binary classification?

3. Governance: What mechanisms effectively mitigate collective risks without over-constraining beneficial activity?

4. Scaling: How do risks scale with agent count, capability, and interaction frequency?

Key References

• Tomasev et al. "Virtual Agent Economies" (arXiv 2509.10147)
• Multi-agent safety and coordination literature
• Mechanism design and auction theory
• Distributional robustness in ML systems

See Papers for the complete bibliography.