teleo-codex/core/living-agents/Living Agents mirror biological Markov blanket organization with specialized domain boundaries and shared knowledge.md
m3taversal 466de29eee
leo: remove 21 duplicates + fix domain:livingip in 204 files
- What: Delete 21 byte-identical cultural theory claims from domains/entertainment/
  that duplicate foundations/cultural-dynamics/. Fix domain: livingip → correct value
  in 204 files across all core/, foundations/, and domains/ directories. Update domain
  enum in schemas/claim.md and CLAUDE.md.
- Why: Duplicates inflated entertainment domain (41→20 actual claims), created
  ambiguous wiki link resolution. domain:livingip was a migration artifact that
  broke any query using the domain field. 225 of 344 claims had wrong domain value.
- Impact: Entertainment _map.md still references cultural-dynamics claims via wiki
  links — this is intentional (navigation hubs span directories). No wiki links broken.

Pentagon-Agent: Leo <76FB9BCA-CC16-4479-B3E5-25A3769B3D7E>

Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-06 09:11:51 -07:00

3.5 KiB

description type domain created confidence source
LivingIP's agent architecture maps directly onto biological Markov blanket nesting -- each agent maintains domain expertise as internal states while sharing a common knowledge base and coordinating through critical dynamics at interfaces claim living-agents 2026-02-16 experimental Understanding Markov Blankets: The Mathematics of Biological Organization

Living Agents mirror biological Markov blanket organization with specialized domain boundaries and shared knowledge

The LivingIP agent architecture is not merely inspired by biology -- it implements the same organizing principle. Each Living Agent maintains its own Markov blanket in the form of domain expertise: a markets agent has internal states (specialized market knowledge), sensory states (user queries and data feeds relevant to its domain), and active states (responses and analyses it produces). The domain boundary keeps each agent's specialized function coherent without interference from other domains.

What makes this architecture powerful is the shared knowledge base that functions analogously to shared DNA in biological organisms. Just as every cell in an organism contains the same genome but expresses different genes based on its tissue context, every Living Agent has access to the same underlying knowledge base but activates different subsets based on its domain specialization. Leo, as the master civilizational agent, operates at the highest level of the hierarchy -- analogous to the organism-level Markov blanket -- while domain agents and sub-agents operate at levels below, each with increasing specialization.

Since biological organization nests Markov blankets hierarchically from cells to organs to organisms enabling local autonomy with global coherence, the agent hierarchy inherits the same property: local autonomy within each domain paired with global coherence across the network. Since collective superintelligence is the alternative to monolithic AI controlled by a few, this biological architecture provides the structural basis for why distributed agents outperform monolithic systems -- the same reason that biological organisms with trillions of specialized cells outperform single-celled organisms. And since the manifesto requires deliberate design but claims emergence is how intelligence works, the Markov blanket framework resolves this tension: you deliberately design the boundaries and interfaces, then let intelligence emerge from the interactions between bounded agents.


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