this repository contains a atari game named cartpole that implement with tensorflow. more detail about cartpole can be avaliable at https://gym.openai.com/envs/CartPole-v0/.
a short description of deep Q-network(dqn): this is a learning case of reinforcemnt learning algorithm deep Q-network,which mainly consits of two componet,an eval network and a target network. deep Q-network use replay buffer to replay exisit game playing experience obtained by a e-greedy policy.the input of dqn is the state of environment,and it's output is the probability distribution of actions.
If you want to run the examples, you'll also have to install:
references: 1.Playing Atari with Deep Reinforcement Learning, Mnih et al., 2013
2.Human-level control through deep reinforcement learning, Mnih et al., 2015