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andrewztan
1475600c81
* removed ddpg2 * removed ddpg2 from codebase * added tests used in ddpg vs ddpg2 comparison * added notes about training timesteps to yaml files * removed ddpg2 yaml files * removed unnecessary configs from yaml files * removed unnecessary configs from yaml files * moved pendulum, mountaincarcontinuous, and halfcheetah tests to tuned_examples * moved pendulum, mountaincarcontinuous, and halfcheetah tests to tuned_examples * added more configuration details to yaml files * removed random starts from halfcheetah
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1.5 KiB
ReStructuredText
23 lines
1.5 KiB
ReStructuredText
Ray RLlib: Scalable Reinforcement Learning
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==========================================
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Ray RLlib is an RL execution toolkit built on the Ray distributed execution framework. See the `user documentation <http://ray.readthedocs.io/en/latest/rllib.html>`__ and `paper <https://arxiv.org/abs/1712.09381>`__.
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RLlib includes the following reference algorithms:
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- Proximal Policy Optimization (`PPO <https://github.com/ray-project/ray/tree/master/python/ray/rllib/ppo>`__) which is a proximal variant of `TRPO <https://arxiv.org/abs/1502.05477>`__.
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- Policy Gradients (`PG <https://github.com/ray-project/ray/tree/master/python/ray/rllib/pg>`__).
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- Asynchronous Advantage Actor-Critic (`A3C <https://github.com/ray-project/ray/tree/master/python/ray/rllib/a3c>`__).
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- Deep Q Networks (`DQN <https://github.com/ray-project/ray/tree/master/python/ray/rllib/dqn>`__).
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- Deep Deterministic Policy Gradients (`DDPG <https://github.com/ray-project/ray/tree/master/python/ray/rllib/ddpg>`__).
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- Ape-X Distributed Prioritized Experience Replay, including both `DQN <https://github.com/ray-project/ray/blob/master/python/ray/rllib/dqn/apex.py>`__ and `DDPG <https://github.com/ray-project/ray/blob/master/python/ray/rllib/ddpg/apex.py>`__ variants.
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- Evolution Strategies (`ES <https://github.com/ray-project/ray/tree/master/python/ray/rllib/es>`__), as described in `this paper <https://arxiv.org/abs/1703.03864>`__.
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These algorithms can be run on any OpenAI Gym MDP, including custom ones written and registered by the user.
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