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OrnsteinUhlenbeckNoise

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OrnsteinUhlenbeckNoise(
   mu: Union[float, th.Tensor] = 0.0, sigma: Union[float, th.Tensor] = 1.0,
   low: float = -1.0, high: float = 1.0, eps: float = 1e-06, theta: float = 0.15,
   dt: float = 0.01
)

Ornstein Uhlenbeck action noise. Based on http://math.stackexchange.com/questions/1287634/implementing-ornstein-uhlenbeck-in-matlab

Args

  • mu (Union[float, th.Tensor]) : Mean of the noise.
  • sigma (Union[float, th.Tensor]) : Standard deviation of the noise.
  • low (float) : The lower bound of the noise.
  • high (float) : The upper bound of the noise.
  • eps (float) : A small value to avoid numerical instability.
  • theta (float) : The rate of mean reversion.
  • dt (float) : Timestep for the noise.
  • stddev_schedule (str) : Use the exploration std schedule.
  • stddev_clip (float) : The exploration std clip range.

Returns

Ornstein-Uhlenbeck noise instance.

Methods:

.sample

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.sample(
   clip: Optional[float] = None, sample_shape: th.Size = th.Size()
)

Generates a sample_shape shaped sample or sample_shape shaped batch of samples if the distribution parameters are batched.

Args

  • clip (Optional[float]) : The clip range of the sampled noises.
  • sample_shape (th.Size) : The size of the sample to be drawn.

Returns

A sample_shape shaped sample.

.reset

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.reset()

Reset the noise.

.mean

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.mean()

Returns the mean of the distribution.

.mode

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.mode()

Returns the mode of the distribution.