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Algorithmic Framework for Model-based Deep Reinforcement Learning with Theoretical Guarantees

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Stochastic Lower Bound Optimization

This is the TensorFlow implementation for the paper Algorithmic Framework for Model-based Deep Reinforcement Learning with Theoretical Guarantees. A PyTorch version will be released later.

Requirements

  1. OpenAI Baselines
  2. rllab (commit number b3a2899)
  3. MuJoCo (1.5)
  4. TensorFlow (>= 1.9)
  5. NumPy (>= 1.14.5)
  6. Python 3.6

Run

Before running, please make sure that rllab and baselines are available

python main.py -c configs/algos/slbo.yml configs/envs/half_cheetah.yml -s log_dir=/tmp

If you want to change hyper-parameters, you can either modify a corresponding yml file or change it temporarily by appending model.hidden_sizes='[1000,1000]' in the command line.

License

See LICENSE for additional details.

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