arXiv:2509.09215v2 Announce Type: replace Abstract: Large language models (LLMs)-empowered autonomous agents are transforming both digital and physical environments by enabling adaptive, multi-agent collaboration. While these agents offer significant opportunities across domains such as finance, healthcare, and smart manufacturing, their unpredictable behaviors and heterogeneous capabilities pose substantial governance and accountability challenges. In this paper, we propose a blockchain-enabled layered architecture for regulatory agent collaboration, comprising an agent layer, a blockchain da
The rapid advancement and deployment of Large Language Models (LLMs) and autonomous agents necessitate immediate attention to their governance and regulatory frameworks.
A strategic reader should care about this as it addresses the critical challenge of governing AI agents, which will dictate their adoption, trust, and integration into vital sectors.
This research introduces architectural solutions for regulatory multi-agent collaboration, moving beyond purely technical development to focus on accountable and governable AI systems.
- · AI Governance Platforms
- · Blockchain Technology Providers
- · Regulatory Bodies
- · Sectors adopting multi-agent systems (finance, healthcare)
- · Unregulated AI Agent Developers
- · Companies with opaque AI systems
- · Traditional compliance frameworks
- · Centralized regulatory models
The adoption of blockchain-enabled regulatory architectures for AI agents will increase transparency and accountability in autonomous systems.
Enhanced trust in AI agent deployments could accelerate their integration into sensitive and mission-critical applications across various industries.
The establishment of global standards derived from such architectural models could lead to new forms of digital international cooperation and regulatory harmonization around AI.
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Read at arXiv cs.AI