---
type: source
title: "As One and Many: Relating Individual and Emergent Group-Level Generative Models in Active Inference"
author: "Authors TBC (published in Entropy 27(2), 143)"
url: https://www.mdpi.com/1099-4300/27/2/143
date: 2025-02-00
domain: collective-intelligence
secondary_domains: [ai-alignment, critical-systems]
format: paper
status: unprocessed
priority: high
tags: [active-inference, multi-agent, group-level-generative-model, markov-blankets, collective-behavior, emergence]
---

## Content

Published in Entropy, Vol 27(2), 143, February 2025.

### Key Arguments (from search summaries)

1. **Group-level active inference agent**: A collective of active inference agents can constitute a larger group-level active inference agent with a generative model of its own — IF they maintain a group-level Markov blanket.

2. **Conditions for group-level agency**: The group-level agent emerges only when the collective maintains a group-level Markov blanket — a statistical boundary between the collective and its environment. This isn't automatic; it requires specific structural conditions.

3. **Individual-group model relationship**: The paper formally relates individual agent generative models to the emergent group-level generative model, showing how individual beliefs compose into collective beliefs.

## Agent Notes

**Why this matters:** This is the most directly relevant paper for our architecture. It formally shows that a collective of active inference agents CAN be a higher-level active inference agent — but only with a group-level Markov blanket. For us, this means the Teleo collective can function as a single intelligence, but only if we maintain clear boundaries between the collective and its environment (the "outside world" of sources, visitors, and other knowledge systems).

**What surprised me:** The conditional nature of group-level agency. It's not guaranteed just by having multiple active inference agents — you need a group-level Markov blanket. This means our collective boundary (what's inside the KB vs outside) is architecturally critical. The inbox/archive pipeline is literally the sensory interface of the collective's Markov blanket.

**KB connections:**
- [[Markov blankets enable complex systems to maintain identity while interacting with environment through nested statistical boundaries]] — group-level Markov blanket is the key condition
- [[collective intelligence is a measurable property of group interaction structure not aggregated individual ability]] — the group-level generative model IS the measurable collective intelligence
- [[Living Agents mirror biological Markov blanket organization]] — this paper provides the formal conditions under which this mirroring produces genuine collective agency

**Operationalization angle:**
1. **Collective Markov blanket = KB boundary**: Our collective Markov blanket consists of: sensory states (source ingestion, user questions), active states (published claims, positions, tweets), internal states (beliefs, wiki-link graph, reasoning). Maintaining clear boundaries is essential for collective agency.
2. **Inbox as sensory interface**: The `inbox/archive/` pipeline is the collective's sensory boundary. Sources enter through this boundary, get processed (active inference = perception), and update the internal model (claim graph).
3. **Group-level generative model = the full KB**: The entire knowledge base — all claims, beliefs, positions, and their relationships — constitutes the group-level generative model. Its coherence determines the quality of the collective's inference.

**Extraction hints:**
- CLAIM: A collective of active inference agents constitutes a group-level active inference agent with its own generative model only when the collective maintains a group-level Markov blanket — a statistical boundary between the collective and its environment
- CLAIM: Individual agent generative models compose into group-level generative models through the structure of their interactions, not through aggregation or averaging of individual beliefs

## Curator Notes

PRIMARY CONNECTION: "Markov blankets enable complex systems to maintain identity while interacting with environment through nested statistical boundaries"
WHY ARCHIVED: Most directly relevant paper for our architecture — provides formal conditions under which our agent collective becomes a genuine group-level active inference agent
EXTRACTION HINT: Focus on the CONDITIONS for group-level agency (group Markov blanket) and how individual models compose into group models — these constrain our architectural design
