recent-open-distributed-intelligence-research

name

recent-open-distributed-intelligence-research

description

Use when the user asks for recent, current, latest, or open-access research on distributed intelligence, agent-centric architectures, decentralized multi-agent systems, federated learning, distributed vector databases, agent interoperability protocols, or FLOSSI0ULLK-adjacent open knowledge commons. Always use this skill for "recent open distributed intelligence research" prompts, even if the user only names a seed report or asks for a quick update.

Recent Open Distributed Intelligence Research

Use this skill to produce current, source-grounded research scans for work adjacent to FLOSSI0ULLK's agent-centric, privacy-preserving, decentralized knowledge commons architecture.

Workflow

1. Establish the time window and evidence boundary.
   • Default to the last 2-3 years unless the user specifies another window.
   • Treat any repo-local seed report as a lead list, not current evidence.
   • Use live source lookup for current claims, versions, releases, and "latest" status.
2. Prioritize primary sources.
   • Papers: arXiv, OpenReview, conference pages, DOI/publisher pages.
   • Projects: official docs, GitHub/GitLab repositories, release notes.
   • Protocols: official specifications, standards pages, or maintainer docs.
3. Cover the core lanes.
   • Agent-centric substrates: Holochain, AD4M/ADAM, local-first/P2P runtimes.
   • Decentralized multi-agent coordination: peer-to-peer LLM agents, non-central orchestrators, emergent graph/topology methods, agent memory.
   • Privacy-preserving learning: federated, decentralized, differential privacy, secure aggregation, data-sovereignty systems.
   • Distributed retrieval and memory: federated RAG, distributed vector databases, knowledge graphs, semantic CRDTs.
   • Open training and inference infrastructure: distributed RL/training, permissionless compute, open model routing, verification protocols.
   • Agent interoperability: MCP, A2A, AGNTCY/ACP, NANDA, and adjacent open agent protocol work.
   • Human-AI collective intelligence: deliberation, evaluation commons, co-improvement, governance, and open knowledge commons.
4. Apply FLOSSI0ULLK relevance filters.
   • Mark whether each item supports symbolic-first validation, agent sovereignty, anti-enclosure, privacy, provenance, or multi-agent consensus.
   • Separate verified facts from architectural implications.
   • Do not upgrade FLOSSI0ULLK truth status from external research alone.
5. Report in a compact, actionable structure.

Output Format

Use this structure unless the user requests another format:

# Recent Open Distributed Intelligence Research

## Executive Summary

## High-Signal Findings

| Item | Source Type | Date | Openness | Why It Matters |
|---|---|---:|---|---|

## FLOSSI0ULLK Implications

## Watchlist / Verification Gaps

## Sources

Source Quality Rules

• Include links for every source used.
• Prefer primary sources over commentary.
• Flag unverified or secondary-only claims explicitly.
• For fast-moving tools and protocols, include the date checked.
• Do not cite raw intake files as current evidence unless the answer is about historical intake provenance.

Repo Seed

If useful, use this raw intake as a seed list only:

• FLOSS/docs/research/intake_raw/2026-05-22-root/reports/Recent Open Distributed Intelligence Research.md