How does the GF(3) conservation law work within this skill?

It ensures that operations like world-hopping and skill dispersal maintain logical balance across attacker, defender, and arbiter roles using balanced ternary logic (mod 3).

What role do ACSets play in this skill?

Attributed C-sets (ACSets) provide the underlying data model, allowing for rigid, category-theoretic representations of world states, agent skills, and their relationships.

What is the primary purpose of Plurigrid ASI Integrated?

It serves as a meta-orchestrator that unifies multiple specialized skills into a structured, mathematically-grounded system for complex task execution.

What is the Glass Bead Game synthesis feature?

It is a high-level coordination method that connects different skills via morphisms, enabling Claude to perform cross-domain reasoning between disparate fields like Type Theory and Infrastructure.

Plurigrid ASI Integrated

Name: Plurigrid ASI Integrated
Author: plurigrid

byplurigrid

•

Data Science & ML

Orchestrates a topological system of specialized skills using category theory, ternary logic, and autonomous synthesis protocols.

About

Plurigrid ASI Integrated is a sophisticated meta-skill designed to unify diverse domain-specific capabilities into a coherent lattice of operations. Leveraging Algebraic Julia (ACSets), ternary logic (GF(3)), and the 'Glass Bead Game' synthesis pattern, it enables autonomous skill dispersal and world-hopping across complex knowledge domains. It is particularly useful for developers and researchers working at the intersection of category theory, scientific computing, and advanced AI orchestration where structural consistency and mathematical rigor are paramount.

Key Features

Unified Skill Lattice Orchestration
GF(3) Balanced Ternary Logic Conservation
Glass Bead Synthesis for Cross-Domain Integration
2 GitHub stars
ACSet-based Data Modeling via AlgebraicJulia
Autonomous Skill Dispersal via Bisimulation Games

Use Cases

Synchronizing distributed skill sets across different mathematical and scientific domains
Ensuring structural consistency in AI-driven knowledge synthesis projects
Coordinating complex multi-agent workflows using topological data structures

About

Key Features

Unified Skill Lattice Orchestration
GF(3) Balanced Ternary Logic Conservation
Glass Bead Synthesis for Cross-Domain Integration
2 GitHub stars
ACSet-based Data Modeling via AlgebraicJulia
Autonomous Skill Dispersal via Bisimulation Games

Use Cases

Synchronizing distributed skill sets across different mathematical and scientific domains
Ensuring structural consistency in AI-driven knowledge synthesis projects
Coordinating complex multi-agent workflows using topological data structures