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https://github.com/Farama-Foundation/Gymnasium.git
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84 lines
2.9 KiB
Python
84 lines
2.9 KiB
Python
"""``StickyAction`` wrapper - There is a probability that the action is taken again."""
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from __future__ import annotations
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from typing import Any
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import gymnasium as gym
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from gymnasium.core import ActType, ObsType
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from gymnasium.error import InvalidProbability
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__all__ = ["StickyAction"]
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class StickyAction(
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gym.ActionWrapper[ObsType, ActType, ActType], gym.utils.RecordConstructorArgs
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):
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"""Adds a probability that the action is repeated for the same ``step`` function.
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This wrapper follows the implementation proposed by `Machado et al., 2018 <https://arxiv.org/pdf/1709.06009.pdf>`_
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in Section 5.2 on page 12.
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No vector version of the wrapper exists.
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Example:
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>>> import gymnasium as gym
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>>> env = gym.make("CartPole-v1")
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>>> env = StickyAction(env, repeat_action_probability=0.9)
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>>> env.reset(seed=123)
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(array([ 0.01823519, -0.0446179 , -0.02796401, -0.03156282], dtype=float32), {})
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>>> env.step(1)
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(array([ 0.01734283, 0.15089367, -0.02859527, -0.33293587], dtype=float32), 1.0, False, False, {})
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>>> env.step(0)
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(array([ 0.0203607 , 0.34641072, -0.03525399, -0.6344974 ], dtype=float32), 1.0, False, False, {})
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>>> env.step(1)
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(array([ 0.02728892, 0.5420062 , -0.04794393, -0.9380709 ], dtype=float32), 1.0, False, False, {})
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>>> env.step(0)
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(array([ 0.03812904, 0.34756234, -0.06670535, -0.6608303 ], dtype=float32), 1.0, False, False, {})
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Change logs:
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* v1.0.0 - Initially added
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"""
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def __init__(
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self, env: gym.Env[ObsType, ActType], repeat_action_probability: float
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):
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"""Initialize StickyAction wrapper.
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Args:
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env (Env): the wrapped environment
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repeat_action_probability (int | float): a probability of repeating the old action.
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"""
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if not 0 <= repeat_action_probability < 1:
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raise InvalidProbability(
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f"repeat_action_probability should be in the interval [0,1). Received {repeat_action_probability}"
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)
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gym.utils.RecordConstructorArgs.__init__(
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self, repeat_action_probability=repeat_action_probability
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)
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gym.ActionWrapper.__init__(self, env)
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self.repeat_action_probability = repeat_action_probability
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self.last_action: ActType | None = None
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def reset(
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self, *, seed: int | None = None, options: dict[str, Any] | None = None
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) -> tuple[ObsType, dict[str, Any]]:
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"""Reset the environment."""
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self.last_action = None
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return super().reset(seed=seed, options=options)
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def action(self, action: ActType) -> ActType:
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"""Execute the action."""
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if (
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self.last_action is not None
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and self.np_random.uniform() < self.repeat_action_probability
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):
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action = self.last_action
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self.last_action = action
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return action
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