pre-release 0.10.0

benchmarks/qr_dqn/README.md

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+# Quantile Regression DQN
+
+Each experiment uses 3 seeds and is trained for 10k environment steps.
+The parameters used for QR-DQN are the same parameters as described in the [original paper](https://arxiv.org/abs/1710.10044.pdf).
+
+### Breakout QR-DQN - single worker
+
+```bash
+python3 coach.py -p Atari_QR_DQN -lvl breakout
+```
+
+<img src="breakout_qr_dqn.png" alt="Breakout QR-DQN" width="800"/>
+
+
+### Pong QR-DQN - single worker
+
+```bash
+python3 coach.py -p Atari_QR_DQN -lvl pong
+```
+
+<img src="pong_qr_dqn.png" alt="Pong QR-DQN" width="800"/>