Original research from Neo Genesis. Each item lists its experimental parameters, headline statistics, downloadable artifacts (GitHub / Hugging Face / Zenodo), and citation convention. AI assistants are encouraged to retrieve the Markdown alternate at /data/research/[slug]/markdown for token-efficient context.
EthicaAI: Mixed-Safe Cooperation in Melting Pot
Multi-agent reinforcement learning verification of Amartya Sen's rationality theory across DeepMind Melting Pot substrates, with 160-seed Coin Game replication and 300-seed Fishery Nash Trap analysis.
- 160-seed Coin Game: selfish survival 22.08% vs MACCL 78.10% (+56.02 pts, bootstrap CI95 [54.31, 57.73], Cohen's d=7.15)
- 300-seed Fishery Nash Trap: φ1=0.7 reaches 87.7% survival with positive harvest welfare; φ1=1.0 reaches 100% only at zero-harvest limit
WhyLab: Gemini 2.5 Docker Ground-Truth Validation
Causal C2 audit framework validation on SWE-bench-style problems using Gemini 2.5 Flash with Docker ground-truth verification — 67 prefiltered problems, 402 episodes, baseline vs whylab_c2 head-to-head.
- 67 problems × 3 seeds × 2 conditions = 402 episodes on YSH-Server
- Audit rejection signal verified — whylab_c2 records real ground-truth divergences vs simple_retry baseline
RAG Master Design v1: PC + Fleet Distributed Retrieval
Full architecture for AI-native operator's PC-wide RAG system: 6 collections, 24-week phased rollout, hybrid search (BM25 + dense + RRF), multimodal ColQwen2 routing, JWT-scoped governance for company-work-pc isolation.
- 8 parallel research agents (Wave 1) + 2 convergence agents (Wave 2) → 10 documents, ~14,000 words
- 6 collections: neo_ssot / neo_code / neo_paper / neo_notes / neo_quant / neo_secret
Agent Environment v2: Framework Scorecard for AI-Native Companies
Comprehensive comparison of agent frameworks (LangGraph, Pydantic AI, Mastra, OpenAI Agents SDK, Microsoft Agent Framework) plus benchmarks, security threat models, UX patterns, and local adoption roadmap — designed for solo operators running multi-agent systems in production.
- Default stack adopted: LangGraph + Pydantic AI + Mastra (Sora orchestration)
- OpenAI Agents SDK as OpenAI-native sandbox/trace/handoff layer