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SAC algorithm (#282)

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* SAC algorithm

* SAC - updates to agent (learn_from_batch), sac_head and sac_q_head to fix problem in gradient calculation. Now SAC agents is able to train.
gym_environment - fixing an error in access to gym.spaces

* Soft Actor Critic - code cleanup

* code cleanup

* V-head initialization fix

* SAC benchmarks

* SAC Documentation

* typo fix

* documentation fixes

* documentation and version update

* README typo
This commit is contained in:
guyk1971
2019-05-01 18:37:49 +03:00
committed by shadiendrawis
parent 33dc29ee99
commit 74db141d5e
92 changed files with 2812 additions and 402 deletions
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README.md
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@@ -25,11 +25,11 @@ coach -p CartPole_DQN -r
<img src="img/doom_health.gif" alt="Doom Health Gathering"/> <img src="img/minitaur.gif" alt="PyBullet Minitaur" width = "249" height ="200"/> <img src="img/ant.gif" alt="Gym Extensions Ant"/>
<br><br>
Blog posts from the Intel® AI website:
* [Release 0.8.0](https://ai.intel.com/reinforcement-learning-coach-intel/) (initial release)
* [Release 0.9.0](https://ai.intel.com/reinforcement-learning-coach-carla-qr-dqn/)
* [Release 0.10.0](https://ai.intel.com/introducing-reinforcement-learning-coach-0-10-0/)
* [Release 0.11.0](https://ai.intel.com/rl-coach-data-science-at-scale) (current release)
* [Release 0.11.0](https://ai.intel.com/rl-coach-data-science-at-scale)
* Release 0.12.0 (current release)
Contacting the Coach development team is also possible through the email [coach@intel.com](coach@intel.com)
@@ -277,6 +277,7 @@ dashboard
* [Clipped Proximal Policy Optimization (CPPO)](https://arxiv.org/pdf/1707.06347.pdf) | **Multi Worker Single Node** ([code](rl_coach/agents/clipped_ppo_agent.py))
* [Generalized Advantage Estimation (GAE)](https://arxiv.org/abs/1506.02438) ([code](rl_coach/agents/actor_critic_agent.py#L86))
* [Sample Efficient Actor-Critic with Experience Replay (ACER)](https://arxiv.org/abs/1611.01224) | **Multi Worker Single Node** ([code](rl_coach/agents/acer_agent.py))
* [Soft Actor-Critic (SAC)](https://arxiv.org/abs/1801.01290) ([code](rl_coach/agents/soft_actor_critic_agent.py))
### General Agents
* [Direct Future Prediction (DFP)](https://arxiv.org/abs/1611.01779) | **Multi Worker Single Node** ([code](rl_coach/agents/dfp_agent.py))