No racing line supplied.
No victories scripted.
A fresh controller. A curved road. Let's see what experience changes.
BIOLOGICAL INTELLIGENCE / EXPERIMENT 003
A tiny brain. Learning to drive.
An embodied learning experiment. Observe every input, error and breakthrough.
No racing line supplied.
No victories scripted.
A fresh controller. A curved road. Let's see what experience changes.
Human practice · excluded from learning and records. ← → steer, ↑ accelerate, ↓ brake. Release to coast.
FROM CRASHES TO CORNERS
Every point is a real attempt in this simulation.
Some days, learning looks like going backwards.
THE SCOREBOARD
20 held-out starts per controller. Same track and surface, learning frozen.
| ATTEMPT | OUTCOME | DISTANCE | TIME | EXPLORATION |
|---|---|---|---|---|
| Start the engine to open the notebook. | ||||
ONE BODY. ANOTHER WAY TO LEARN.
The controller observes lateral position, heading error, road curvature and speed. It receives no ideal racing line and no prerecorded steering sequence.
Nine combinations of steering and throttle move a simplified vehicle. The anatomical fly's wheel and pedals display those same inputs in real time.
Tabular Q-learning rewards forward progress and penalizes leaving the track. Action values persist between attempts; outcomes emerge from the simulation.
This browser study uses an engineered Q-learning controller and road-relative vehicle physics, not a running whole-brain connectome. NeuroMechFly / FlyGym anatomy supplies the articulated fly. The FlyWire atlas of 139,255 neurons and 54.5 million synapses informs our longer-term biological integration work.
Fixed 0.12-second model steps. An attempt ends on a full lap, an off-track exit, or 216 simulated seconds. A fresh study resets memory. Human practice is isolated. Evaluation freezes learning and tests both policies with 2% exploration on held-out initial conditions. Faster playback changes wall-clock speed only.
Inspect the model ↗ · Previous foraging study ↗COMMUNITY-FUNDED EXPERIMENTS
Planned for Robinhood Chain: a share of token trading fees supports future experiments, with holders helping choose research directions. Funding and governance are in development.