日志即代理:ActiveGraph--事件溯源反应图实现可审计可分叉的智能体系统
阅读原文· arxiv.orgActiveGraph 是一个反转传统代理框架的运行时,将只追加的事件日志作为真相来源,工作图是日志的确定性投影。普通函数、类或 LLM 支持的例程等行为对图变化做出反应并发出新事件,组件间完全通过共享图协调,无需直接指令。该设计实现三个特性:从日志确定性重放任意运行、在任意事件低成本分叉运行且不重复共享前缀、以及从高层目标到单个模型调用的端到端溯源。项目以 Apache-2.0 开源,附带快速启动演示、确定性重放、分叉对比和溯源追踪功能。
Computer Science > Artificial Intelligence
Title:The Log is the Agent: Event-Sourced Reactive Graphs for Auditable, Forkable Agentic Systems
Abstract:Most agent frameworks are built around the language model: a conversation loop comes first, then tools, then rules, and finally a logging layer bolted on for observability, with state persisted as retrievable "memory." We describe ActiveGraph, a runtime that inverts this arrangement. The append-only event log is the source of truth; the working graph is a deterministic projection of that log; and behaviors--ordinary functions, classes, LLM-backed routines, or logic attached to typed edges--react to changes in the graph and emit new events. No component instructs another; coordination happens entirely through the shared graph. This single design decision yields three properties that retrieval-and-summarization memory systems do not provide: deterministic replay of any run from its log, cheap forking that branches a run at any event without re-executing the shared prefix, and end-to-end lineage from a high-level goal down to the individual model call that produced each artifact. We present the architecture, a determinism contract that makes replay sound, and a worked diligence example whose full causal structure is reconstructable from the log alone. We discuss--without claiming to demonstrate--why this substrate is unusually well suited to self-improving agents, and how it extends the BabyAGI lineage and prior graph-memory research.
| Comments: | |
| Subjects: | Artificial Intelligence (cs.AI); Multiagent Systems (cs.MA) |
| Cite as: | arXiv:2605.21997 [cs.AI] |
| (or arXiv:2605.21997v1 [cs.AI] for this version) | |
| https://doi.org/10.48550/arXiv.2605.21997 arXiv-issued DOI via DataCite |
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