rlberry.envs
.gym_make¶
- rlberry.envs.gym_make(id, wrap_spaces=False, **kwargs)[source]¶
Same as gym.make, but wraps the environment to ensure unified seeding with rlberry.
- Parameters:
- idstr
Environment id.
- wrap_spacesbool, default = False
If true, also wraps observation_space and action_space using classes in rlberry.spaces, that define a reseed() method.
- **kwargskeywords arguments
Additional arguments to pass to the gymnasium environment constructor.
Examples
>>> from rlberry.envs import gym_make >>> env_ctor = gym_make >>> env_kwargs = {"id": "CartPole-v1"} >>> env = env_ctor(**env_kwargs)
Examples using rlberry.envs.gym_make
¶
Compare PPO and A2C on Acrobot with AdaStop
Compare PPO and A2C on Acrobot with AdaStop
A demo of DQN algorithm in CartPole environment
A demo of DQN algorithm in CartPole environment
A demo of M-DQN algorithm in CartPole environment
A demo of M-DQN algorithm in CartPole environment