Skip to content

docs(exploration): prior-art L2/L3 — Chinese-community supplement #30

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
cyber-ayi merged 1 commit into from
Jun 6, 2026
Merged

docs(exploration): prior-art L2/L3 — Chinese-community supplement #30

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
52 changes: 50 additions & 2 deletions exploration/prior-art-l2-l3.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -35,6 +35,7 @@ carry biases (reward/optimization) we must **not** adopt given autotelic-not-rew
| **Hermes** (NousResearch) | provider-agnostic, **local-first** (Ollama/LM Studio) | local "fallback brain" (privacy routing, adr-0006 rule 6) | needs ≥64k ctx; no world precedent |
| **Voyager / ODYSSEY / MindForge / Co-Voyager** | Minecraft open-world agents: **auto-curriculum + skill library** | reference architecture for open-world exploration | **skill-acquisition + curriculum = reward-shaped → conflicts with adr-0004**; reference only |
| **PIANO** (Project Sid / Altera) | parallel multi-stream cognition; agents **generate own goals** from social motivation; 1000+ agents | good **L3** reference (multi-stream + self-generated goals) | civilization/multi-agent framing; not a single-dyad harness |
| **AgentScope** (Alibaba DAMO, Apache-2.0) | Python multi-agent framework; **`msghub` broadcast** + pipeline orchestration; official 7-agent Werewolf game template; Ollama / local-LLM friendly | **multi-agent comms primitive** — closest thing to a "drop N agents into a room" runtime; useful for the multi-agent substrate option in [[substrate-evennia-multi-agent]] | workflow/task-oriented; less *persistent-world* precedent than Eliza — needs a world layer above |

## L3 — cognition / memory / autotelic motivation

Expand All @@ -44,6 +45,44 @@ carry biases (reward/optimization) we must **not** adopt given autotelic-not-rew
| **Letta/MemGPT · Mem0** | tiered memory (core/recall/archival), auto promote/compress | **memory infrastructure off the shelf** | memory layer only; no drive/identity |
| **autotelic line** (Colas; **MAGELLAN** ICML'25; "Beyond Utility" NeurIPS'25) | agents self-generate NL goals; MAGELLAN uses **learning-progress (LP)** to guide goal choice | goal-generation machinery = the selector's theoretical core | **LP is an intrinsic reward → still optimizing**; borrow the mechanism, **drop the optimization objective** |
| **needs / personality / artificial life** (**Sophia** 2512.18202; "personality from **needs alone**"; evolving_personality; SPeCtrum) | personality/behavior **emerging from basic needs**; persistent identity | closest to the identity+needs engine | social-emergence framing; known **persona drift** + convergence to "average persona" |
| **GenerativeAgentsCN** (x-glacier, MIT, 463⭐) | Smallville Chinese reimplementation; **verified Ollama + Qwen3-4B / DeepSeek-R1 running 25 agents** locally | **concrete local-LLM cost evidence** for an N≥25 multi-agent run + a ready zh scaffold; fork-and-run start for multi-agent emergence work | still Smallville-shaped (schedules/goals) — same optimization framing as Park 2023 |
| **AgentVerse — `simulation` track** (OpenBMB/Tsinghua, arxiv 2308.10848) | LLM multi-agent framework split into `task-solving` + `simulation`; Minecraft branch studies emergent multi-agent behavior | third multi-agent-emergence reference besides Smallville/PIANO; cleaner sim/task separation than ElizaOS | not autotelic — sim runs still framed by task success |
| **EconAgent** (Tsinghua, ACL'24 Outstanding) | 100 LLM agents × 20 simulated years; macro-economic sim that **reproduces stylized economic facts** | strongest existing evidence that a **long-horizon multi-LLM sim can stay coherent** — supports the "non-optimal believable long-horizon" feasibility | optimization-shaped objective (macro outcomes) → borrow the coherence-evidence, not the objective |

## Chinese-community supplement (added 2026-06-06)

Section added after the original note converged. Covers Chinese-ecosystem
items that sit alongside the L2/L3 tables — role-LLM model layer, RP corpora,
and MUD assets — plus a relevant consumer-product observation. The new L2/L3
rows above (AgentScope, GenerativeAgentsCN, AgentVerse-sim, EconAgent) belong
in their tables; this subsection is for the items that don't.

- **CharacterGLM-6B** (THU CoAI + Lingxin AI, EMNLP'24, open 6B) — Chinese
role-customised dialogue **pre-trained** model with a six-dimension subjective
evaluator. Candidate **NPC local model** when role-fidelity matters more than
general capability; slots beneath the L3 table as a model-layer choice.
- **Chinese RP / role-eval corpora**: ChatHaruhi (54k dialogues, 32 zh+en
characters, MIT) · CharacterEval (1785 multi-turn dialogues, 77 zh
novel/drama characters) · RoleBench · SuperCLUE-Role. Collectively the
largest open Chinese role-fidelity dataset stack. Reusable as (a) NPC
persona-fidelity evaluator, (b) drive-layer believability evaluator,
(c) RAG corpus for character knowledge.
- **Wuxia-MUD lib assets** (pkuxkx.net wiki + `mudcore` / `xwjy_mud/mudcore`):
30 years of LPMud-based Chinese MUD content — characters / sects / techniques
/ geography / NPC dialogue — usable as RAG corpus *if* a Chinese-setting
substrate is chosen. Setting choice is left to [[substrate-evennia-multi-agent]];
the asset's existence is the relevant prior-art fact.
- **AI-companion product observation** (informative, not adoptable): closed-
source Chinese RP apps — 筑梦岛 (Yuewen/Tencent), 猫箱 (ByteDance), 星野
(MiniMax), Tavo — all ship "multi-AI characters in one shared scene" features.
**Multi-agent co-presence has consumer-product validation in the zh market**
that the en market lacks — a weak signal that the operator-in-multi-agent-world
UX is not unprecedented (relevant to [[substrate-evennia-multi-agent]]).
- **One MUD × LLM lead** — `mud.ren/threads/436` describes a project called
"Yanhuang MUD" (炎黄 MUD) running `npc_manager.py` for LLM NPCs with memory +
knowledge-base retrieval. No GitHub repo surfaced; appears to be single-NPC,
not multi-agent. The **only public Chinese MUD + LLM signal found**; worth
contacting the thread author if multi-agent MUD work proceeds.

## Two tensions

Expand All @@ -65,6 +104,9 @@ carry biases (reward/optimization) we must **not** adopt given autotelic-not-rew
loop + memory + world precedent, TS) — *strip the crypto*; **OpenClaw** for
browser/CDP + the operator async gateway when needed; **Hermes** as the local-first
fallback brain. Voyager/PIANO are **reference architectures only** (reward bias).
**AgentScope** is a newly surfaced multi-agent-comms candidate (`msghub` + Werewolf
template); merits a spike comparison vs ElizaOS-core *only if* the multi-agent
substrate option in [[substrate-evennia-multi-agent]] is pursued.
- **L3 (self-build — it's the IP — but stand on giants):** reuse **Generative Agents**
memory+reflection + **Letta/Mem0** for storage; take goal-generation from
**Colas/MAGELLAN** but **cut the learning-progress reward**; take identity+needs
Expand All @@ -86,8 +128,14 @@ carry biases (reward/optimization) we must **not** adopt given autotelic-not-rew
- Commit the L2 runtime choice → a `harness runtime` ADR (resolves the ROADMAP gate).
- T4 will likely spawn its own exploration (selector design without an optimization
objective; memory/identity stack choice).
- **Multi-agent substrate spike** (gated by [[substrate-evennia-multi-agent]]): fork
`GenerativeAgentsCN`, measure token/tick at N=25 with Qwen3-4B on operator's local
hardware; only then is AgentScope-vs-ElizaOS-core comparison decisive.
- Contact `mud.ren/threads/436` author re: "Yanhuang MUD" — the single public
zh MUD × LLM lead; cheap, may yield code or design insight.

## Sources

- L2: [ElizaOS](https://www.elizaos.ai/) · [ElizaOS/OpenClaw/Hermes compared](https://innfactory.ai/en/blog/openclaw-vs-hermes-agent-comparison/) · [OpenClaw browser harness](https://openclawlaunch.com/guides/openclaw-browser-harness) · [Hermes Agent](https://github.com/nousresearch/hermes-agent) · [Voyager](https://voyager.minedojo.org/) · [ODYSSEY](https://openreview.net/pdf?id=vtGLtSxtqv) · [MindForge](https://arxiv.org/pdf/2411.12977) · [Project Sid / PIANO](https://arxiv.org/abs/2411.00114)
- L3: [Generative Agents](https://arxiv.org/pdf/2304.03442) · [Letta/MemGPT vs Mem0](https://vectorize.io/articles/mem0-vs-letta) · [Augmenting Autotelic Agents w/ LLMs (Colas)](https://proceedings.mlr.press/v232/colas23a/colas23a.pdf) · [Colas publications (MAGELLAN)](https://cedriccolas.com/publications/) · [LLM Agents Beyond Utility](https://arxiv.org/abs/2510.14548) · [Sophia: Persistent Agent Framework for Artificial Life](https://arxiv.org/pdf/2512.18202) · [Personality from needs alone](https://www.eurekalert.org/news-releases/1099709) · [SPeCtrum identity](https://arxiv.org/pdf/2502.08599)
- L2: [ElizaOS](https://www.elizaos.ai/) · [ElizaOS/OpenClaw/Hermes compared](https://innfactory.ai/en/blog/openclaw-vs-hermes-agent-comparison/) · [OpenClaw browser harness](https://openclawlaunch.com/guides/openclaw-browser-harness) · [Hermes Agent](https://github.com/nousresearch/hermes-agent) · [Voyager](https://voyager.minedojo.org/) · [ODYSSEY](https://openreview.net/pdf?id=vtGLtSxtqv) · [MindForge](https://arxiv.org/pdf/2411.12977) · [Project Sid / PIANO](https://arxiv.org/abs/2411.00114) · [AgentScope](https://github.com/modelscope/agentscope)
- L3: [Generative Agents](https://arxiv.org/pdf/2304.03442) · [Letta/MemGPT vs Mem0](https://vectorize.io/articles/mem0-vs-letta) · [Augmenting Autotelic Agents w/ LLMs (Colas)](https://proceedings.mlr.press/v232/colas23a/colas23a.pdf) · [Colas publications (MAGELLAN)](https://cedriccolas.com/publications/) · [LLM Agents Beyond Utility](https://arxiv.org/abs/2510.14548) · [Sophia: Persistent Agent Framework for Artificial Life](https://arxiv.org/pdf/2512.18202) · [Personality from needs alone](https://www.eurekalert.org/news-releases/1099709) · [SPeCtrum identity](https://arxiv.org/pdf/2502.08599) · [GenerativeAgentsCN](https://github.com/x-glacier/GenerativeAgentsCN) · [AgentVerse](https://github.com/OpenBMB/AgentVerse) (paper: [arxiv 2308.10848](https://arxiv.org/abs/2308.10848)) · [EconAgent (ACL'24)](https://aclanthology.org/2024.acl-long.829/)
- Chinese-community supplement: [CharacterGLM-6B](https://github.com/thu-coai/CharacterGLM-6B) · [Chat-Haruhi-Suzumiya](https://github.com/LC1332/Chat-Haruhi-Suzumiya) · [CharacterEval](https://arxiv.org/abs/2401.01275) · [RoleBench / RoleLLM](https://github.com/InteractiveNLP-Team/RoleLLM-public) · [SuperCLUE-Role](https://github.com/CLUEbenchmark/SuperCLUE-Role) · [pkuxkx wiki](https://www.pkuxkx.net/wiki) · [mudcore](https://gitee.com/mudcore/mudcore) · [mudchina站点列表](https://mudchina.github.io/) · [mud.ren/threads/436 — 炎黄 MUD](https://mud.ren/threads/436) · [筑梦岛](https://zhumengdao.com/) · [猫箱 (ByteDance)](https://www.maoxiang.com/)
Loading