Situational Logic: Building NOT, OR, and AND Gates with Slime Mazes

Physarum logic demos treat growth paths as computational outputs. Inputs are encoded through geometry and stimulus placement, while observed route outcomes are mapped to gate truth behavior.

How gates are implemented

• Maze architecture defines possible routes.
• Attractants and repellents bias route selection.
• Final occupancy pattern is interpreted as logical output.

This can demonstrate NOT, OR, and AND behavior in controlled simple setups.

What works well

Single-gate demos and shortest-path outcomes can be consistent enough for educational and proof-of-concept use.

Why scaling breaks

Connecting many gates compounds variability.

• Biological noise and environmental sensitivity increase output drift.
• Timing alignment across branches becomes fragile.
• Physical state changes can alter the effective circuit while running.

So complex multi-gate bio-circuits remain a hard open problem.

Best use today

Treat slime logic gates as experimental computation models and teaching tools, not as drop-in replacements for electronic logic stacks.

Related reading: Lego Maze Caveat, Slime Algorithms, and Bio-Computing.