This branch is the code for QUOTA with continuous action in the paper

QUOTA: The Quantile Option Architecture for Reinforcement Learning
Shangtong Zhang, Borislav Mavrin, Linglong Kong, Bo Liu, Hengshuai Yao (AAAI 2019)

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├── Dockerfile                                      # Dependencies
├── requirements.txt                                # Dependencies
├── dist-ddpg.py                                    # Entrance for the Roboschool experiments
|   ├── option_ddpg_continuous                      # Entrance of QUOTA
├── deep_rl/agent/QuantileOptionDDPG_agent.py       # Implementation of QUOTA with continuous action
├── deep_rl/agent/QuantileDDPG_agent.py             # Implementation of QR-DDPG 
└── plot_dist-ddpg.py                               # Plotting

I can send the data for plotting via email upon request.

This branch is based on the DeepRL codebase and is left unchanged after I completed the paper. Algorithm implementations not used in the paper may be broken and should never be used. It may take extra effort if you want to rebase/merge the master branch.