让AI行动前先提交承诺书，确保安全可审计。
OpenKedge: Governing Agentic Mutation with Execution-Bound Safety and Evidence Chains
- 用声明式意图+执行合约控制AI行为，防止随意修改状态。
- 在多智能体冲突中成功仲裁竞争请求，杜绝危险操作。
- 通过证据链追踪每一步操作，适合高安全需求的系统。
自主AI代理的兴起暴露出以API为中心架构的根本缺陷：概率系统在缺乏上下文、协调与安全保证的情况下直接执行状态变更。我们提出OpenKedge协议，将状态变更重新定义为受控过程而非API调用的直接结果。该协议要求参与者提交声明式意图提案，在执行前基于确定性系统状态、时间信号和策略约束进行评估。获批意图被编译为执行合约，严格限定可执行动作、资源范围和时限，并通过临时任务身份强制执行。这将安全机制从被动过滤转变为预防性的执行绑定。关键的是，OpenKedge引入了意图到执行的证据链（IEEC），以密码学方式链接意图、上下文、策略决策、执行边界与结果，形成统一的可追溯链。这使状态变更变为可验证、可重建的过程，支持确定性审计与系统行为推理。我们在多智能体冲突场景和云基础设施变更中评估了OpenKedge，结果表明该协议能确定性地仲裁竞争意图，遏制不安全执行，同时保持高吞吐量，为大规模安全运行智能体系统提供了原则性基础。
原文摘要 · Abstract (English)
The rise of autonomous AI agents exposes a fundamental flaw in API-centric architectures: probabilistic systems directly execute state mutations without sufficient context, coordination, or safety guarantees. We introduce OpenKedge, a protocol that redefines mutation as a governed process rather than an immediate consequence of API invocation. OpenKedge requires actors to submit declarative intent proposals, which are evaluated against deterministically derived system state, temporal signals, and policy constraints prior to execution. Approved intents are compiled into execution contracts that strictly bound permitted actions, resource scope, and time, and are enforced via ephemeral, task-oriented identities. This shifts safety from reactive filtering to preventative, execution-bound enforcement. Crucially, OpenKedge introduces an Intent-to-Execution Evidence Chain (IEEC), which cryptographically links intent, context, policy decisions, execution bounds, and outcomes into a unified lineage. This transforms mutation into a verifiable and reconstructable process, enabling deterministic auditability and reasoning about system behavior. We evaluate OpenKedge across multi-agent conflict scenarios and cloud infrastructure mutations. Results show that the protocol deterministically arbitrates competing intents and cages unsafe execution while maintaining high throughput, establishing a principled foundation for safely operating agentic systems at scale.
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