Train AI to play Atari Enduro

A Reinforcement Learning (DQN) based AI agent

Posted by bythew3i on December 12, 2019

During the 2019 Thanksgiving break, I trained a DQN based agent which can play Enduro atari game.

Game Rule

The number of cars you must pass is posted at the beginning of each day in the lower right corner of your instrument panel (200 on the first day, 300 on subsequent days). Each time you pass a car, this meter counts off by one. When you pass the required number of cars, green flags appear. But keep going. All additional kilometres are added to your total. You’ll move on to the next day when the present day ends. If you don’t pass the required number of cars by daybreak, the game ends.

Requirements

tensorflow==1.14.0 numpy==1.16.4 gym==0.15.4 keras-rl matplotlib

Results

After 1.5 hours training, I get these results: episode_reward_500000 episode_steps_500000

)ter 10 hours training, I get these results: episode_reward_4000000 episode_steps_4000000

Demo