Reinforcement Learning in Helicopter Game
This is a proof of concept RL implementation for a helicopter game. The helicopter learns to avoid obstacles by learning a reward function based on Radial Basis Clustering.
Compile
You should have qt4 or qt5 and a c++ compiler. Type the following commands in shell:
qmake
make
Usage
Run the runnable output of make. Then,
Press
<space> to pause/resume
<S> to save clusters
<P> to switch to autpilot mode
<I> to save episode
<L> to load clusters
<G> to start learning in background mode
<R> to switch to replay mode (then use forward and backward to jump 1000 episodes forward or backward
Train on background and replay
- Press 'I' to enable saving episodes. They will be saved in './episodes/' folder.
- Press 'G' to run background training and wait until finishing...
- When it is done, press 'R' to replay. press left/right arrow keys to move 1000 episodes back/forward in the player.