docs(exploration): prior-art L2/L3 — Chinese-community supplement#30
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A separate research pass surfaced five concrete zh-ecosystem items the original survey missed; the most load-bearing is GenerativeAgentsCN — a Smallville reimplementation that empirically validates 25 LLM agents running on local Ollama + Qwen3-4B / DeepSeek-R1, which materially de-risks the local-cost question for any future multi-agent substrate work. L2/L3 table additions: - L2: AgentScope (Alibaba DAMO, Apache-2.0) — msghub multi-agent broadcast + pipeline; official 7-agent Werewolf template; closest off-the-shelf "drop N agents into a room" runtime. Flagged for spike vs ElizaOS-core only if the multi-agent substrate option is pursued. - L3: GenerativeAgentsCN (x-glacier, MIT) — Smallville zh fork with verified Ollama + Qwen3-4B / DeepSeek-R1 at N=25. Concrete local-LLM cost evidence. - L3: AgentVerse simulation track (OpenBMB/Tsinghua, arxiv 2308.10848) — third multi-agent-emergence reference besides Smallville/PIANO. - L3: EconAgent (Tsinghua, ACL'24 Outstanding) — 100 LLM × 20-yr macro sim reproducing stylized facts. Strongest evidence that long-horizon multi-LLM sims can stay coherent — supports the "non-optimal believable long-horizon" feasibility (separate from objective). Chinese-community supplement subsection (don't fit the L2/L3 dichotomy): - CharacterGLM-6B (THU CoAI + Lingxin, EMNLP'24, open 6B) — Chinese role-customised pre-trained dialogue model; NPC local-model candidate. - Chinese RP corpora — ChatHaruhi (54k), CharacterEval (1785/77), RoleBench, SuperCLUE-Role; reusable as persona-fidelity / believability evaluator + RAG corpus. - Wuxia-MUD lib assets (pkuxkx.net wiki + mudcore) — 30 yrs of LPMud zh content as RAG corpus if a zh-setting substrate is chosen (setting choice deferred to substrate-evennia-multi-agent). - AI-companion product observation — 筑梦岛/猫箱/星野/Tavo ship multi-AI-in-one-scene features; zh-market consumer validation of multi-agent co-presence UX. Closed-source — informative only. - One MUD × LLM lead: mud.ren/threads/436 'Yanhuang MUD' (炎黄 MUD) — the only public zh MUD + LLM signal found; single-NPC + no GitHub. Worth contacting author if multi-agent MUD work proceeds. Recommendations + Open items updated to gate the AgentScope spike behind the upcoming substrate-evennia-multi-agent exploration; note's overall status stays converging (lean unchanged: ElizaOS-core + OpenClaw + Hermes). Session-Id: 019e9e62-7e3f-7286-9de2-7b3bc7b9369d Agent: cc-rc-bot
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Summary
Supplements
exploration/prior-art-l2-l3.mdwith five concrete items the original 2026-06-03 survey missed, all surfaced by a Chinese-community-focused research pass.Most load-bearing finding: GenerativeAgentsCN (x-glacier, MIT, 463⭐) — Smallville zh reimplementation that empirically validates 25 LLM agents running on local Ollama + Qwen3-4B / DeepSeek-R1. Materially de-risks the local-cost question if/when a multi-agent substrate is considered. Companion exploration note (
substrate-evennia-multi-agent) is being opened in parallel and links here.What's added
L2 table (one row) — AgentScope (Alibaba DAMO, Apache-2.0). msghub multi-agent broadcast + 7-agent Werewolf template; closest off-the-shelf "drop N agents into a room" runtime. Flagged for spike vs ElizaOS-core only if the multi-agent substrate option is pursued.
L3 table (three rows):
simulationtrack (OpenBMB/Tsinghua, arxiv 2308.10848) — third multi-agent-emergence reference besides Smallville/PIANO.New "Chinese-community supplement" subsection — items that don't fit the L2/L3 dichotomy:
mud.ren/threads/436"Yanhuang MUD" (炎黄 MUD),npc_manager.py. Only public zh MUD+LLM signal found; single-NPC, no GitHub. Worth contacting the author if multi-agent MUD work proceeds.Recommendations + Open items updated to gate the AgentScope spike behind the upcoming
[[substrate-evennia-multi-agent]]exploration. Note's overall status staysconverging; the L2 lean (ElizaOS-core + OpenClaw + Hermes) is unchanged.Why this and not a new note
Adding to the existing
prior-art-l2-l3.mdrather than spawning a parallelprior-art-l2-l3-cn.mdbecause (a) the L2/L3 categorization is the same, (b) the dataset is the same lineage (community/research work mapped to our needs), and (c) splitting by geography would bias future readers' mental indexing. The supplement is dated + headed for transparency about when it was added.Test plan
[[substrate-evennia-multi-agent]]resolves once the companion PR lands.harness-cisignal (will run as path-filtered; should be green — no harness/ touched).🤖 Generated with Claude Code