Skip to content
Algorithmic Framework for Model-based Deep Reinforcement Learning with Theoretical Guarantees
Branch: master
Clone or download
Latest commit c963d6e Dec 28, 2018
Permalink
Type Name Latest commit message Commit time
Failed to load latest commit information.
configs copyright update Nov 28, 2018
lunzi update help description Dec 27, 2018
slbo copyright Dec 2, 2018
CODE_OF_CONDUCT.md release Nov 28, 2018
CONTRIBUTING.md release Nov 28, 2018
LICENSE release Nov 28, 2018
README.md Update README.md Nov 28, 2018
main.py copy right Nov 28, 2018
requirements.txt release Nov 28, 2018
rllab_requirements.txt release Nov 28, 2018

README.md

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.

You can’t perform that action at this time.