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from rlkit.exploration_strategies.base import RawExplorationStrategy | |
import numpy as np | |
class GaussianStrategy(RawExplorationStrategy): | |
""" | |
This strategy adds Gaussian noise to the action taken by the deterministic policy. | |
Based on the rllab implementation. | |
""" | |
def __init__(self, action_space, max_sigma=1.0, min_sigma=None, | |
decay_period=1000000): | |
assert len(action_space.shape) == 1 | |
self._max_sigma = max_sigma | |
if min_sigma is None: | |
min_sigma = max_sigma | |
self._min_sigma = min_sigma | |
self._decay_period = decay_period | |
self._action_space = action_space | |
def get_action_from_raw_action(self, action, t=None, **kwargs): | |
sigma = ( | |
self._max_sigma - (self._max_sigma - self._min_sigma) * | |
min(1.0, t * 1.0 / self._decay_period) | |
) | |
return np.clip( | |
action + np.random.normal(size=len(action)) * sigma, | |
self._action_space.low, | |
self._action_space.high, | |
) | |