A deterministic randomization toolkit with seeded streams, statistical distributions, and gameplay selection systems.

Designed for gameplay systems that require repeatable results, isolated substreams, loot control, and procedural logic.

Seeded Streams • Statistical Distributions • Gameplay Selection Systems • Deterministic Shuffle • Bag Fairness

Same Seed × Same Sequence × Same Call Order = Same Results

Full explanation in documentation PDF.

Add RNG³ nodes → Create or Seed Stream → Draw / Fork / Build

RNG³ is a deterministic randomization toolkit for Unreal Engine that gives Blueprint users seeded streams, weighted selection, float distributions, deterministic shuffling, index sampling, and bag-based fairness. Use it to build repeatable gameplay systems, isolate loot/AI/procedural logic into separate substreams, and reduce Blueprint spaghetti.

100% FREE FOR THE UNREAL ENGINE DEVELOPER COMMUNITY!!

PLEASE PURCHASE THE PROFESSIONAL VERSION OF THE PLUGIN AS THE PRICE IS THE SAME AS THE PERSONAL VERSION

Calculation

Use one stream for an entire system, split it into deterministic substreams, or combine multiple selection methods together.

• Deterministic Stream

• Forked Substreams

• Weighted Selection

• Shuffle / Sample

• Bag Random Fairness

• Chance

Usage

Use a single stream, or combine multiple deterministic systems together.
(1) Stream Variable [Required]
(2) Bag State [Optional / Required for bag draws]
(3) Sequence / Child Sequence [Optional for stream separation]
(4) Label [Optional for deterministic forks]

Features

• Works with Blueprint gameplay systems that require deterministic random behavior

• Seeded stream creation with debug-visible Seed, Sequence, and Draw Count

• Deterministic stream forking using labels and child sequences

• Independent substreams for isolating gameplay systems

• Integer, unsigned integer, and float random draws

• Float distributions: Uniform, Triangular, Normal (Gaussian), Exponential

• Weighted index selection for loot tables, rarity tables, and probability-driven choices

• Deterministic Fisher-Yates shuffle for repeatable ordering

• Deterministic sampling with or without replacement

• Bag-based fairness randomizer for reduced repeats and controlled rotations

• Ideal for loot systems, AI variation, spawn selection, procedural events, card draws, playlists, and replay-safe gameplay systems

• Includes example Blueprint and example level

• Built entirely in C++

Video Example: COMING SOON

Note: Most issues arise from changing call order, modifying sequence values, or mixing multiple gameplay systems into the same stream.