Added doc page for SACD
This commit is contained in:
parent
610fd3dcf6
commit
d97dbc727c
|
|
@ -35,6 +35,7 @@ RL Baselines3 Zoo also offers a simple interface to train, evaluate agents and d
|
||||||
modules/ppo_mask
|
modules/ppo_mask
|
||||||
modules/ppo_recurrent
|
modules/ppo_recurrent
|
||||||
modules/qrdqn
|
modules/qrdqn
|
||||||
|
modules/sacd
|
||||||
modules/tqc
|
modules/tqc
|
||||||
modules/trpo
|
modules/trpo
|
||||||
|
|
||||||
|
|
|
||||||
|
|
@ -0,0 +1,99 @@
|
||||||
|
.. _sacd:
|
||||||
|
|
||||||
|
.. automodule:: sb3_contrib.sacd
|
||||||
|
|
||||||
|
|
||||||
|
SACD
|
||||||
|
====
|
||||||
|
|
||||||
|
|
||||||
|
`Soft Actor Critic Discrete (SACD) <https://arxiv.org/abs/1910.07207>`_ is a modification of the original Soft Actor Critic Algorithm for discrete action spaces.
|
||||||
|
|
||||||
|
.. rubric:: Available Policies
|
||||||
|
|
||||||
|
.. autosummary::
|
||||||
|
:nosignatures:
|
||||||
|
|
||||||
|
MlpPolicy
|
||||||
|
CnnPolicy
|
||||||
|
MultiInputPolicy
|
||||||
|
|
||||||
|
|
||||||
|
Notes
|
||||||
|
-----
|
||||||
|
|
||||||
|
- Original paper: https://arxiv.org/abs/1910.07207
|
||||||
|
- Original Implementation: https://github.com/p-christ/Deep-Reinforcement-Learning-Algorithms-with-PyTorch
|
||||||
|
|
||||||
|
|
||||||
|
Can I use?
|
||||||
|
----------
|
||||||
|
|
||||||
|
- Recurrent policies: ❌
|
||||||
|
- Multi processing: ✔️
|
||||||
|
- Gym spaces:
|
||||||
|
|
||||||
|
|
||||||
|
============= ====== ===========
|
||||||
|
Space Action Observation
|
||||||
|
============= ====== ===========
|
||||||
|
Discrete ✔️ ✔️
|
||||||
|
Box ❌ ✔️
|
||||||
|
MultiDiscrete ❌ ✔️
|
||||||
|
MultiBinary ❌ ✔️
|
||||||
|
Dict ❌ ✔️
|
||||||
|
============= ====== ===========
|
||||||
|
|
||||||
|
|
||||||
|
Example
|
||||||
|
-------
|
||||||
|
.. code-block:: python
|
||||||
|
|
||||||
|
import gymnasium as gym
|
||||||
|
|
||||||
|
from sb3_contrib import SACD
|
||||||
|
|
||||||
|
env = gym.make("CartPole-v1", render_mode="rgb_array")
|
||||||
|
|
||||||
|
model = SACD("MlpPolicy", env, verbose=1, policy_kwargs=dict(net_arch=[64,64]))
|
||||||
|
model.learn(total_timesteps=20_000)
|
||||||
|
model.save("sacd_cartpole")
|
||||||
|
|
||||||
|
del model # remove to demonstrate saving and loading
|
||||||
|
|
||||||
|
model = SACD.load("sac_cartpole")
|
||||||
|
|
||||||
|
obs, info = env.reset()
|
||||||
|
while True:
|
||||||
|
action, _states = model.predict(obs, deterministic=True)
|
||||||
|
obs, reward, terminated, truncated, info = env.step(action)
|
||||||
|
if terminated or truncated:
|
||||||
|
obs, info = env.reset()
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
Parameters
|
||||||
|
----------
|
||||||
|
|
||||||
|
.. autoclass:: SACD
|
||||||
|
:members:
|
||||||
|
:inherited-members:
|
||||||
|
|
||||||
|
.. _sac_policies:
|
||||||
|
|
||||||
|
SACD Policies
|
||||||
|
-------------
|
||||||
|
|
||||||
|
.. autoclass:: MlpPolicy
|
||||||
|
:members:
|
||||||
|
:inherited-members:
|
||||||
|
|
||||||
|
.. autoclass:: stable_baselines3.sac.policies.SACPolicy
|
||||||
|
:members:
|
||||||
|
:noindex:
|
||||||
|
|
||||||
|
.. autoclass:: CnnPolicy
|
||||||
|
:members:
|
||||||
|
|
||||||
|
.. autoclass:: MultiInputPolicy
|
||||||
|
:members:
|
||||||
Loading…
Reference in New Issue