---
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: null-result
priority: high
tags: [active-inference, multi-agent, group-level-generative-model, markov-blankets, collective-behavior, emergence]
processed_by: theseus
processed_date: 2026-03-10
extraction_model: "minimax/minimax-m2.5"
extraction_notes: "Extracted three claims from the active inference paper. Two are direct theoretical claims from the paper (group Markov blanket requirement for collective agency; compositional nature of belief aggregation). One is an operationalization claim applying the theory to the Teleo inbox architecture (experimental confidence due to applied nature). The paper provides strong formal grounding for the collective intelligence architecture work."
---

## 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


## Key Facts
- Published in Entropy, Vol 27(2), 143, February 2025
- Paper formally relates individual agent generative models to emergent group-level generative model
- Group-level agency requires specific structural conditions (group-level Markov blanket)
