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joy7758/README.md

Bin Zhang

Independent researcher building Digital Biosphere Architecture for governable AI agents.

I work on a five-layer architecture for increasingly autonomous AI systems, with a focus on persona portability, semantic interaction objects, runtime governance, execution integrity, and audit evidence.

My work focuses on how autonomous AI systems can become

  • Identifiable (persona layer)
  • Interpretable for coordination (interaction layer)
  • Governable (runtime control)
  • Verifiable in execution (execution integrity)
  • Auditable (evidence records)

AI Agent Governance Stack

flowchart LR
    Persona["Persona Layer<br>POP"] --> Interaction["Interaction Layer<br>Agent Intent Protocol"]
    Interaction --> Governance["Governance Layer<br>Token Governor"]
    Governance --> Execution["Execution Integrity Layer<br>MVK"]
    Execution --> Audit["Audit Evidence Layer<br>ARO-Audit"]
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Start Here

Core Projects

POP

Portable persona objects for the Persona Layer.

Agent Intent Protocol (AIP)

Machine-readable intent, action, and result objects for agent runtimes.

Token Governor

Runtime governance and checkpoint control for the Governance Layer.

MVK

Execution integrity and verification-oriented runtime truth for the Execution Integrity Layer.

ARO-Audit

Evidence records, receipts, and reviewable exports for the Audit Evidence Layer.

Verifiable Agent Demo

Minimal cross-layer demonstration that links persona, interaction, governance, execution trace, and audit evidence.

Layer-to-Repository Map

Layer Repository
Persona Layer persona-object-protocol
Interaction Layer agent-intent-protocol
Governance Layer token-governor
Execution Integrity Layer fdo-kernel-mvk
Audit Evidence Layer aro-audit
Cross-layer demo verifiable-agent-demo

Research Direction

This work is not aimed at replacing existing agent frameworks. The focus is on governance-oriented architecture layers that can be attached to AI systems as reusable, inspectable, and standardizable components.

  • Agent Interaction Protocols
  • Semantic Object Communication for AI agents
  • Runtime governance for autonomous AI systems
  • Execution integrity and bounded audit evidence

Identity / links

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  1. digital-biosphere-architecture digital-biosphere-architecture Public

    Architecture overview for the Digital Biosphere ecosystem.

    Python

  2. agent-intent-protocol agent-intent-protocol Public

    Python

  3. persona-object-protocol persona-object-protocol Public

    Persona layer for portable, framework-agnostic AI persona objects.

    Python 1

  4. token-governor token-governor Public

    Governance layer for runtime budget, policy, and trade-off control in AI systems.

    Python 1

  5. aro-audit aro-audit Public

    Audit evidence layer for bounded, reviewable, and replay-oriented AI execution artifacts.

    Python 1

  6. verifiable-agent-demo verifiable-agent-demo Public

    Minimal end-to-end demo for the Digital Biosphere Architecture stack.

    Python