What is the primary purpose of the Unworld skill?

The Unworld skill replaces temporal succession with derivational succession, meaning it uses mathematical seeds rather than an external clock to determine the 'next' state in a sequence.

Can this skill be used for distributed systems?

Yes, because it is frame-invariant and doesn't rely on an external clock, it is ideal for systems where multiple observers need to agree on a sequence of events without synchronized time.

How does Unworld ensure state determinism?

It employs a seed-chaining formula (seed_{n+1} = (seed_n ⊕ (trit_n × γ)) × MIX mod 2⁶⁴) that ensures any position in a chain can be computed or verified based purely on the genesis seed.

What is GF(3) conservation in this context?

GF(3) conservation is an invariant where the sum of trits at any position across triadic streams remains balanced (≡ 0 mod 3), ensuring the algebraic integrity of the system.

Unworld Derivational Engine

Name: Unworld Derivational Engine
Author: plurigrid

byplurigrid

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Data Science & ML

Replaces temporal succession with deterministic seed-chaining to enable verifiable, frame-invariant state transitions.

About

The Unworld skill provides a robust mathematical framework for replacing external temporal clocks with internal derivational chains. By utilizing a specific formula involving the golden ratio and SplitMix64 multipliers, it ensures that every state transition is deterministic and independently verifiable. This is essential for developers working on topological computing, distributed systems, or complex simulations where causality must be derived from logic rather than observer-dependent time. The skill supports triadic streams, GF(3) conservation, and involution verification to maintain algebraic integrity across all derivational sequences.

Key Features

GF(3) balanced color chain generation for algebraic state conservation
Deterministic seed-chaining using Golden Ratio and SplitMix64 constants
Self-inverse involution verification (ι ∘ ι = id)
Nash equilibrium derivation via best-response dynamics
Interleaved triadic streams for multi-threaded derivational logic
2 GitHub stars

Use Cases

Generating deterministic procedural content or algorithmic state transitions
Simulating topological systems where causality is defined by derivation rather than time
Building verifiable state machines for distributed ledgers and decentralized systems

About

Key Features

GF(3) balanced color chain generation for algebraic state conservation
Deterministic seed-chaining using Golden Ratio and SplitMix64 constants
Self-inverse involution verification (ι ∘ ι = id)
Nash equilibrium derivation via best-response dynamics
Interleaved triadic streams for multi-threaded derivational logic
2 GitHub stars

Use Cases

Generating deterministic procedural content or algorithmic state transitions
Simulating topological systems where causality is defined by derivation rather than time
Building verifiable state machines for distributed ledgers and decentralized systems