This branch is the code of TD3 with a uniformly random behavior policy for the paper

Generalized Off-Policy Actor-Critic
Shangtong Zhang, Wendelin Boehmer, Shimon Whiteson (NeurIPS 2019)

Provably Convergent Two-Timescale Off-Policy Actor-Critic with Function Approximation
Shangtong Zhang, Bo Liu, Hengshuai Yao, Shimon Whiteson (ICML 2020)

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├── Dockerfile                                      # Dependencies
├── requirements.txt                                # Dependencies
├── agent/TD3_agent.py                              # A random TD3 agent
└── template_jobs.py.                               # Start random TD3 baseline

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.