The Logic Shores

You have made landfall on The Logic Shores. Ancient Boolean beacons emit raw signal streams across the bay. To navigate further into the archipelago, you must calibrate a Single-Layer Perceptron to classify incoming AND / OR logic states.

CORE CONCEPTS

1. Weighted Inputs (w1, w2):

Scale the strength and orientation of input signals x1 and x2.

2. Threshold Bias (b):

Offsets the decision line up or down to set the firing threshold.

3. Linear Separability:

A straight line dividing points into 0 (OFF) and 1 (ON) regions.

MISSION OBJECTIVE

Adjust w1, w2, and b on the right panel until accuracy reaches 100% for the target gate, then transmit calibration data to the Python Cloudflare Worker.

ARCHIPELAGO_TERMINAL_LOGPORT: 8787

[0.00s] INITIALIZING SECTOR ALPHA-1 TELEMETRY...

[0.12s] PERCEPTRON NODE LINK ESTABLISHED.

[0.15s] AWAITING NAVIGATOR CALIBRATION PARAMETERS.

PERCEPTRON GATE CALIBRATOR

Interactive Single-Layer Neural Node

ARIADNE VOICE TELEMETRY

Single-Layer Perceptrons & Linear Boundaries

A single-layer Perceptron calculates outputs using f(x) = step(w1*x1 + w2*x2 + b). Adjusting weights w1 and w2 rotates the linear decision boundary across the Cartesian coordinate plane, while adjusting bias b translates the boundary to separate boolean logic conditions like AND or OR gates.

PARAMETER TUNINGFormula: y = step(w1·x1 + w2·x2 + b)

Weight w₁ (Input x₁)1.00

Weight w₂ (Input x₂)1.00

Bias b (Threshold Offset)-1.50

TARGET AND TRUTH TABLE CHECK100% ACCURACY

INPUT

TARGET

OUTPUT

STATUS

(0, 0)

✓ PASS

(1, 0)

✓ PASS

(0, 1)

✓ PASS

(1, 1)

✓ PASS

DECISION LINE: 1.0x₁ + 1.0x₂ + -1.5 = 0