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An op for generating noise from a zero-mean Ornstein-Uhlenbeck process.
tf_agents.utils.common.ornstein_uhlenbeck_process(
initial_value,
damping=0.15,
stddev=0.2,
seed=None,
scope='ornstein_uhlenbeck_noise'
)
The Ornstein-Uhlenbeck process is a process that generates temporally correlated noise via a random walk with damping. This process describes the velocity of a particle undergoing brownian motion in the presence of friction. This can be useful for exploration in continuous action environments with momentum.
The temporal update equation is:
x_next = (1 - damping) * x + N(0, std_dev)
Args | |
---|---|
initial_value
|
Initial value of the process. |
damping
|
The rate at which the noise trajectory is damped towards the mean. We must have 0 <= damping <= 1, where a value of 0 gives an undamped random walk and a value of 1 gives uncorrelated Gaussian noise. Hence in most applications a small non-zero value is appropriate. |
stddev
|
Standard deviation of the Gaussian component. |
seed
|
Seed for random number generation. |
scope
|
Scope of the variables. |
Returns | |
---|---|
An op that generates noise. |