Open milesbrundage opened 8 years ago
use env.monitor - it will periodically output video and also will record the stats and prep for uploading to OpenAi Gym
after env = gym.make(env_name) add
env.monitor.start('/tmp/dqn', force=True)
and then add this at the end of the
env.monitor.close()
i can add a pull request if you want
And some other small changes that can be left out. Epsilon annealing can be easily modified to go longer/shorter/faster/slower, and is currently set to go for 99 iterations and then fully exploit during recording every 100th iteration, but that can be removed as well if you want to see what it looks like during exploration.