How does information geometry improve system monitoring?

It applies the Fisher-Rao metric to the immune state manifold, allowing the system to measure 'distance' between states and update beliefs efficiently using natural gradients.

What does GF(3) trit encoding mean in this context?

It uses a three-state logic system (-1 for Self/Tolerate, 0 for Unknown/Inspect, +1 for Non-Self/Attack) to classify signals and ensure system balance through mathematical conservation.

What is the Cybernetic Immune skill used for?

It is used to build systems that can autonomously distinguish between internal 'self' operations and external 'non-self' threats, similar to a biological immune system.

Is this skill suitable for cybersecurity applications?

Yes, its 'Cognitive Firewall' and 'Exafference' detection models are highly effective for identifying novel patterns that deviate from expected system behavior.

Cybernetic Immune System

Name: Cybernetic Immune System
Author: plurigrid

byplurigrid

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データサイエンスとML

Implements a cognitive immune framework using active inference and information geometry for robust system self-maintenance.

概要

The Cybernetic Immune skill provides a specialized architecture for systems to perform self/non-self discrimination based on the principles of autopoiesis, active inference, and perceptual control theory. By leveraging GF(3) trit encoding and Fisher-Rao information metrics, it allows for high-precision anomaly detection (exafference) and homeostatic regulation. This skill is particularly useful for building resilient agentic systems, maintaining data integrity through conservation laws, and simulating complex biological or cognitive defense mechanisms within a categorical cybernetics framework.

主な機能

2 GitHub stars
Information geometry calculations using Fisher-Rao metrics and natural gradients
Categorical cybernetics integration for compositional system coherence
GF(3) trit-based classification for self, unknown, and non-self discrimination
Cognitive firewall coordination for managing system-level threat responses
Active inference modeling for distinguishing reafference from exafference

ユースケース

Developing resilient AI agents that can monitor their own operational integrity
Modeling complex systems that require homeostatic balance and anomaly detection
Designing security protocols based on biological immune response patterns

概要

主な機能

2 GitHub stars
Information geometry calculations using Fisher-Rao metrics and natural gradients
Categorical cybernetics integration for compositional system coherence
GF(3) trit-based classification for self, unknown, and non-self discrimination
Cognitive firewall coordination for managing system-level threat responses
Active inference modeling for distinguishing reafference from exafference

ユースケース

Developing resilient AI agents that can monitor their own operational integrity
Modeling complex systems that require homeostatic balance and anomaly detection
Designing security protocols based on biological immune response patterns