COMPASS: Explainable Agentic Governance Framework

🔑 Enhanced Key Takeaways

• •COMPASS paper was submitted to arXiv on March 11, 2026, as a 22-page document with 4 figures, categorized under Artificial Intelligence (cs.AI).[2]
• •The framework acknowledges current limitations including lack of human-in-the-loop validation and underdeveloped action-selection capabilities, positioning it as a foundational system for future enhancements.[1]
• •Experimental results focus solely on evaluation mechanisms for the four sub-agents, with potential for expansion into full operational capabilities in subsequent iterations.[1]

🛠️ Technical Deep Dive

• •Each sub-agent uses RAG to query domain-specific dynamic knowledge bases stored in Vector DBs, such as latest regulatory texts for the Compliance Agent and real-time energy intensity data for the Carbon Agent.[1]
• •The Orchestrator employs LLM-as-a-judge to assign quantitative scores and generate explainable justifications, enabling real-time arbitration of conflicting objectives across dimensions.[1]
• •Table 1 in the paper provides a comparative analysis of AI governance frameworks, while Table 9 offers qualitative comparisons against existing AI paradigms.[1]

🔮 Future ImplicationsAI analysis grounded in cited sources

⏳ Timeline