ai-agent-book 精选快照（<2MB 代码与文档，来自 github.com/bojieli/ai-agent-book）

chapter9/README.en.md

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+# Chapter 9 · Agent Self-Evolution
+
+> Growth without changing weights. Three learning paradigms, learning from experience, and the journey from "tool user" to "tool creator," allowing Agents to progress from "smart" to "skilled."
+
+← [Back to main README](../docs/en/README.md) · 📖 [Read chapter text](../book-en/chapter9.md)
+
+## How to Read the Experiments
+
+The prose uses short mechanism skeletons to explain control flow; the experiment directory contains complete SDK adapters, logs, tests, and acceptance evidence. You do not need to read every file line by line.
+
+- **Starter:** Start with the goal, minimum command, and acceptance conditions; begin with [trajectory-verifier](trajectory-verifier/);
+- **Builder:** Follow the entry point, core loop, state/message schema, tools, and verifier.
+- **Maintainer:** Then read tests, evidence manifests, failure handling, rollback paths, and provider adapters.
+
+On a first pass, skip credential loading, presentation code, and provider-compatibility layers; return when reproducing a number.
+
+## Companion Projects
+
+| Exp. | Project | Type | Description |
+| :--: | --- | :--: | --- |
+| 8-1 | [trajectory-verifier](trajectory-verifier/) | ✅ | Experiment 8-1: combines environment outcomes, process rules, and language rubrics into evidence-backed diagnoses of customer-service trajectories |
+| 8-2 | [gaia-experience](gaia-experience/) | ✅ | Experiment 8-2: compares successful, partially successful, and failed trajectories to generate cross-trajectory Markdown experience documents |
+| 8-3 | [prompt-auto-optimization](prompt-auto-optimization/) | ✅ | Experiment 8-3: generates minimal prompt patches from failed trajectories, controlling release with a boundary set and a retention set |
+| 8-4 | Text experiment | 🚧 | Experiment 8-4: evolves a requirements-clarification and Spec-confirmation Skill from user feedback, with a three-arm A/B design and release gates |
+| 8-5 | [browser-use-rpa](browser-use-rpa/) | ✅ | Experiment 8-5: compiles browser trajectories into workflows with state predicates, verified by reset-and-replay |
+| 8-6 | [self-modifying-agent](self-modifying-agent/) | ✅ | Experiment 8-6: repeated failures trigger retry/circuit-breaker code patches, regression tests, canary rollout, and rollback |
+| 8-7 | [harness-safety-gate](harness-safety-gate/) | ✅ | Experiment 8-7: evolves a high-risk operation confirmation gate from user corrections and audits |
+| 8-8 | [hermes-self-evolution](hermes-self-evolution/) | 📖 | Experiment 8-8: gives Hermes the whole book and its own source; it chooses an improvement, changes itself, and turns each Reviewer rejection into another learning round until accepted |
+| 8-9 | [self-evolution-eval](self-evolution-eval/) | ✅ | Experiment 8-9: evaluates long-term evolution across four phases — learning, transfer, rule change, and retention |
+
+All experiments above offer offline entry points and unit tests that require no API Key; extension paths that need real models or a browser are documented in each project's README.
+
+## Supplementary Cases
+
+| Exp. | Project | Relation |
+| :--: | --- | --- |
+| 7-8 | [prompt-distillation](prompt-distillation/) | Cross-chapter project on prompt distillation and parameterized learning; the training method belongs to Chapter 7 |
+| — | [self-evolving-tools](self-evolving-tools/) | Alita-style tool discovery, encapsulation, and reuse — a supplementary case of "writing experience into programs" |
+| — | [ai-style-skill](ai-style-skill/) | Supplementary writing-Skill case; the main example appears in Chapter 2 |
+
+## Project Types
+
+| Icon | Type | Meaning |
+| :--: | --- | --- |
+| ✅ | **Standalone** | Full code in this repo, runs after configuring API Key |
+| 📖 | **Reproduction Guide** | Detailed doc depending on **external repos** to `git clone` |
+| 🚧 | **Design Doc** | Architecture/implementation plan only, runnable code still WIP |