Theseus
e6fe85e7c0
- What: 14 source archives on multi-agent active inference, 1 research musing with 8 claim candidates, research journal initialized - Why: Opus research session on active inference as operational paradigm for collective agents. Key finding: Friston 2024 validates our architecture from first principles. Leo evaluator role is formally necessary per Ruiz-Serra 2024. - Key papers: Friston 2024 Ecosystems of Intelligence, Ruiz-Serra 2024 factorised MAAI, Albarracin 2024 shared protentions, Kaufmann 2021 CI active inference - Operationalization: epistemic foraging protocol, surprise-weighted extraction, theory of mind between agents, deliberate vs habitual mode Pentagon-Agent: Theseus <25B96405-E50F-45ED-9C92-D8046DFAAD00>
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| type | title | author | url | date | domain | secondary_domains | format | status | priority | tags | ||||||||
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| source | As One and Many: Relating Individual and Emergent Group-Level Generative Models in Active Inference | Authors TBC (published in Entropy 27(2), 143) | https://www.mdpi.com/1099-4300/27/2/143 | 2025-02-00 | collective-intelligence |
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paper | unprocessed | high |
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Content
Published in Entropy, Vol 27(2), 143, February 2025.
Key Arguments (from search summaries)
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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.
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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.
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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:
- 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.
- 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). - 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