Chapter 10 · Multi-Agent Collaboration

Collective intelligence can surpass individual intelligence. Multi-Agent classification framework, when it truly outperforms a single Agent, collaboration with and without shared context, failure modes, and the emergent "Agent Society."

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Companion Projects

Exp.	Project	Type	Description
10-1	staged-system-prompt	✅	The same Coding Agent loads different system prompts and tool sets at different execution stages of a task (requirements clarification → code implementation → code review). This allows it to play different roles and exhibit different behaviors within a single conversation, while the dialogue history and task state are continuously shared between stages. If the review fails, it can fall back to the implementation stage.
10-2	multi-role-transfer	✅	Demonstrates chained handoff under a shared context: a single session contains multiple specialized role agents, each with its own system prompt and dedicated tool set. Using a transfer_to_agent tool, an agent autonomously decides when to switch to another role based on task progress. Because they share the same dialogue history, the complete context is naturally preserved during handoff.
10-3	book-translation	✅	The formal 26-unit dual-arm run translates an illustrated, code-heavy technical-book sample and passes all 12 gates, including quality, context, token, latency, resource, checkpoint, receipt, and provenance comparisons.
10-4	TalkAct reproduction record + use-computer-while-calling/	📖	The retained 16/16-episode Anthropic-caller campaign passes all 17 gates. Both arms achieved 1.0 task success; duplex reduced median voice latency from 12.52 s to 2.32 s (5.40×), while the control had higher probe correctness and lower mean wall time. Because the Gemini credential was invalid, this run used TalkAct's supported Anthropic Sonnet caller override and must not be silently pooled with default-Gemini upstream results.
10-5	autonomous-phone-registration	✅	A real LLM autonomously selected the Phone Agent, and the formal run passed all 9 gates over Playwright, bidirectional WebRTC/RTP, local TTS/Whisper, validation and re-asking, concurrent ask/fill, privacy, and one authorized localhost submission. The manuscript does not require PSTN/E.164.
10-6	parallel-web-research	✅	N independent Playwright browser sessions search ten real university sites while a real LLM extracts cited evidence. Saved acceptance covers monitoring, timeout/error isolation, single settlement, cascading termination acknowledgements, resource cleanup, and a measured 3.142× same-site parallel speedup.
10-7	generative_agents/	📖	Stanford's "AI town" generative agents (companion to Experiment 10-7); external repository joonspk-research/generative_agents, which you need to clone yourself (see the main README appendix).
10-8	voice-werewolf	🚧	Adds a real-LLM user simulator that sees only its seat context, must call tools, and enters only through synthesized audio plus real OpenRouter audio ASR. Strict revalidation rejected two early arms that mistook a bad transcript for abstention; unaffected v2 passes E2E, isolation, rule winner, and three cycles, but fails strategy after a Villager wrongly exiles the Seer.
## 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
🚧	In Progress	Implementation or required acceptance evidence is incomplete; runnable code may exist but is not a full acceptance claim