Flappy Bird, trained
Q-learning and SARSA learn when to flap, then face narrower pipe gaps to test generalization.
Agent replay
Recorded agents
How it works.
Discretize the world
Reduce positions and velocities to a compact tabular state space.
From the original project.
Saved artifacts · click to inspect
Original artifact ↗
Original artifact ↗
Original artifact ↗
Original artifact ↗
Continue in the source.
Follow the source README for the original runtime, dependencies, data, and configuration.
git clone https://github.com/eforus-overseer/FlappyBird-RL-Agent.gitRead the setup and requirements ↗Project artifacts.
Source links point to the original public repository. Credit belongs to the project authors and the dependencies credited there.