parameter_noise.py

import numpy as np


class AdaptiveParamNoise(object):
    def __init__(self, initial_stddev=0.1, desired_action_stddev=0.1, adoption_coefficient=1.01):
        self.initial_stddev = initial_stddev
        self.desired_action_stddev = desired_action_stddev
        self.adoption_coefficient = adoption_coefficient

        self.current_stddev = initial_stddev

    def adapt(self, distance):
        if distance > self.desired_action_stddev:
            # Decrease stddev.
            self.current_stddev /= self.adoption_coefficient
        else:
            # Increase stddev.
            self.current_stddev *= self.adoption_coefficient
        return self.current_stddev

    def get_stats(self):
        stats = {
            'param_noise_stddev': self.current_stddev,
        }
        return stats

    def __repr__(self):
        fmt = 'AdaptiveParamNoiseSpec(initial_stddev={}, desired_action_stddev={}, adoption_coefficient={})'
        return fmt.format(self.initial_stddev, self.desired_action_stddev, self.adoption_coefficient)