What is braincraft?

rougier/braincraft — explained in plain English

Analysis updated 2026-07-17 · repo last pushed 2026-03-04

★ 195PythonAudience · researcherComplexity · 4/5MaintainedSetup · hard

Mindmap

mindmap
  root((braincraft))
    What it does
      Neural network competition
      Controls simulated robot
      Finds energy sources
      Five staged challenges
    Tech stack
      Python
      Echo State Network
      Simulation environment
    Use cases
      Learn neural dynamics
      Practice reinforcement learning
      Study sensorimotor control
    Audience
      Researchers
      Robotics hobbyists
      Neuroscience students

mindmap root((braincraft)) What it does Neural network competition Controls simulated robot Finds energy sources Five staged challenges Tech stack Python Echo State Network Simulation environment Use cases Learn neural dynamics Practice reinforcement learning Study sensorimotor control Audience Researchers Robotics hobbyists Neuroscience students

What do people build with it?

USE CASE 1

Design and train a small neural network to control a simulated robot under strict time limits.

USE CASE 2

Experiment with genetic algorithms or reinforcement learning to solve a sensorimotor control task.

USE CASE 3

Study how Echo State Networks handle memory and decision-making in a constrained robotics challenge.

USE CASE 4

Submit a pull request to compete in an open-source, invitation-based robotics competition.

What is it built with?

Python

How does it compare?

	rougier/braincraft	cvlab-kaist/gld	fxyz666/logicpipe
Stars	195	196	196
Language	Python	Python	Python
Last pushed	2026-03-04	—	—
Maintenance	Maintained	—	—
Setup difficulty	hard	hard	hard
Complexity	4/5	5/5	5/5
Audience	researcher	researcher	researcher

Figures from each repo's GitHub metadata at analysis time.

How do you get it running?

Difficulty · hard Time to first run · 1h+

Requires understanding fixed neural dynamics equations and building a self-contained training pipeline within a strict 100-second compute limit.

No license information was mentioned in the explanation.

Copy-paste prompts

Prompt 1

Explain how an Echo State Network could be trained in 100 seconds to steer a robot toward an energy source using distance and color sensor inputs.

Prompt 2

Help me design a genetic algorithm to train a 1000-neuron controller for a simulated maze-navigating robot with steering limited to 5 degrees per step.

Prompt 3

Walk me through the two equations that govern neural activity flow in an Echo State Network so I can implement one from scratch.

Prompt 4

Suggest a self-contained reinforcement learning approach that doesn't rely on pre-trained models, suitable for a robot with only steering as its output.

Frequently asked questions