Welcome to Deepair’s documentation!¶
Deepair (/diːp er/) is a Python library that have reliable implementations of Deep reinforcement learning algorithms.
Simple way to start¶
Install deepair with pip
pip install deepair
start with gym env
import gym
from deepair.dqn import Rainbow
env = gym.make('LunarLander-v2')
rain = Rainbow(env=env, memory_size=10000, batch_size=32, target_update=256)
rain.train(timesteps=200000)
# test
state = env.reset()
done = False
score = 0
while not done:
action = rain.select_action(state, deterministic=True)
next_state, reward, done, info = env.step(action)
state = next_state
score += reward
print("score: ", score)
