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47 lines
1.9 KiB
Python
47 lines
1.9 KiB
Python
#
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# Copyright (c) 2017 Intel Corporation
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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import numpy as np
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from exploration_policies.exploration_policy import *
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class AdditiveNoise(ExplorationPolicy):
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def __init__(self, tuning_parameters):
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"""
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:param tuning_parameters: A Preset class instance with all the running paramaters
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:type tuning_parameters: Preset
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"""
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ExplorationPolicy.__init__(self, tuning_parameters)
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self.variance = tuning_parameters.exploration.initial_noise_variance_percentage
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self.final_variance = tuning_parameters.exploration.final_noise_variance_percentage
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self.decay_steps = tuning_parameters.exploration.noise_variance_decay_steps
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self.variance_decay_delta = (self.variance - self.final_variance) / float(self.decay_steps)
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def decay_exploration(self):
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if self.variance > self.final_variance:
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self.variance -= self.variance_decay_delta
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elif self.variance < self.final_variance:
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self.variance = self.final_variance
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def get_action(self, action_values):
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if self.phase == RunPhase.TRAIN:
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self.decay_exploration()
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action = np.random.normal(action_values, 2 * self.variance * self.action_abs_range)
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return action #np.clip(action, -self.action_abs_range, self.action_abs_range).squeeze()
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def get_control_param(self):
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return self.variance
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