DQN/ and DoubleDQN/ implement the same environment set with batched
environment wrappers, replay buffers, Q-networks, agents, configurations, and
training entrypoints.
| Algorithm | Target | TensorFlow implementation |
|---|---|---|
| DQN | (r + \gamma\max_a Q_{\bar\theta}(s',a)) | Tensor batches, replay sampling, target networks, GradientTape, tf.function |
| Double DQN | (r + \gamma Q_{\bar\theta}(s',\arg\max_a Q_\theta(s',a))) | Separate online/target action roles in the agent update |
CartPole and Acrobot include test scripts. Training files also contain
TensorBoard summary code. No training score is documented here because the
repository does not retain a benchmark report as source.