Neuro-Symbolic Participation Governance for Verifiable AI Agents in Open Digital Twin Ecosystems

• URL: http://arxiv.org/abs/2608.00937v1
• Date: Sun, 02 Aug 2026 02:30:32 GMT
• Title: Neuro-Symbolic Participation Governance for Verifiable AI Agents in Open Digital Twin Ecosystems
• Abstract summary: Existing multi-agent systems often lack robust verification for identity, capability, and policy compliance.<n>This paper proposes a neuro-symbolic decentralized governance framework for verifiable agents in collaborative digital twin environments.<n>Our findings suggest that neuro-symbolic decentralized governance provides a scalable and trustworthy pathway for safe human-machine collaboration.
• Score: 12.774828297549467
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Autonomous AI agents, increasingly empowered by large language models, are becoming important components of human-machine systems for high-stakes decision support in digital twin ecosystems. However, existing multi-agent systems often lack robust verification for identity, capability, and policy compliance, especially in decentralized environments spanning multiple institutions. This paper proposes a neuro-symbolic decentralized governance framework for verifiable agents in collaborative digital twin environments. By representing agents through multi-layer semantic profiles, the framework bridges probabilistic neural reasoning with deterministic institutional governance, thereby supporting trustworthy human-AI collaboration and meaningful human oversight. Capabilities are grounded in formal domain ontologies to enable machine-interpretable, policy-aware, and context-sensitive participation. These credentials, issued by organizational authorities, are validated via blockchain-based smart contracts, ensuring auditable participation without exposing sensitive data. We demonstrate the framework using a decision-support prototype with clinic, digital twin, and wearable provider agents effectively prevents unauthorized interaction and enforces institutional policies with manageable overhead. Our findings suggest that neuro-symbolic decentralized governance provides a scalable and trustworthy pathway for safe human-machine collaboration across institutional boundaries.

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