Classify self/non-self signatures using GF(3) trit encoding and Fisher-Rao geometry.
npx skills add https://github.com/plurigrid/asi --skill cybernetic-immune
Please help me install this Agent Skill. Skill: cybernetic-immune Source: https://github.com/plurigrid/asi/tree/main/skills/cybernetic-immune Command: npx skills add https://github.com/plurigrid/asi --skill cybernetic-immune
Models self/non-self discrimination using reafference, GF(3) trit encoding, and information geometry to simulate immune-like decision processes.
Just run a basic self/non-self discrimination demo with the default GF(3) setup.
High-intent search queries and answers about installing and using this skill.
Self/non-self discrimination uses reafference and exafference signals to classify entities as SELF, UNKNOWN, or NON-SELF. This Skill applies GF(3) trit encoding and Fisher-Rao information geometry to simulate immune-like decision processes that map signatures to tolerance, inspection, or attack responses in real-time.
GF(3) trit encoding maps three immune states—SELF (-1), UNKNOWN (0), and NON-SELF (+1)—onto Galois Field arithmetic. This approach enables compact representation and natural gradient updates via Fisher-Rao geometry, making it efficient for simulating immune networks and AI agents requiring regulated responses to novel stimuli.
Yes. This Skill performs self/non-self discrimination on simulated immune networks, cognitive firewall orchestrations, and AI agents. It provides parallel-processing workflows, colorSignature tagging, memory mechanisms, and decision rules that enable real-time classification and regulated responses in safety-critical contexts.
Information geometry, specifically Fisher-Rao geometry, provides a natural metric for learning trajectories on probability manifolds. This Skill uses natural gradient updates and parallel transport along geodesics to approximate learning in immune systems, enabling more stable and geometrically grounded model refinement than Euclidean methods.
The Skill includes parallel transport and cytokine signal propagation workflows that model immune responses along information-geometric geodesics. These mechanisms, combined with colorSignature tagging, recognize functions, and memory components, enable coordinated decision-making across distributed immune network agents.
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