Structuring multi-agent governance using the CASE enterprise control architecture combined with LLM constitutional rules prevents the decay of agent epistemic integrity during prolonged multi-agent consensus negotiations.

Adversarial Debate Score

51% survival rate under critique

Supporting Research Papers

• The CASE Framework: A Multi-Disciplinary Control Architecture for Governing Enterprise Agentic AI

  Enterprises are deploying autonomous AI agents faster than they can govern them, and prevailing approaches stretch a single discipline, typically DevSecOps built for deterministic automation, across e...

• LLM Constitutional Multi-Agent Governance

  Large Language Models (LLMs) can generate persuasive influence strategies that shift cooperative behavior in multi-agent populations, but a critical question remains: does the resulting cooperation re...

• Position: A Three-Layer Probabilistic Assume-Guarantee Architecture Is Structurally Required for Safe LLM Agent Deployment

  This position paper argues that enforcing LLM agent safety within a single abstraction layer is not merely suboptimal but categorically insufficient for deployed LLM agents -- a structural consequence...

• AGENTSAFE: A Unified Framework for Ethical Assurance and Governance in Agentic AI

  The rapid deployment of large language model (LLM)-based agents introduces a new class of risks, driven by their capacity for autonomous planning, multi-step tool integration, and emergent interaction...

• Emergent Collusion in Long-Horizon LLM Agent Interaction

  LLM agents are increasingly deployed in collaborative settings, yet long-term interaction may give rise to undesirable coordination. We study the emergence of collusion in a long-horizon multi-agent e...

Literature Assessment

Formal Verification

Source