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BCQ variant on top of DDQN (#276)

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* kNN based model for predicting which actions to drop
* fix for seeds with batch rl
This commit is contained in:
Gal Leibovich
2019-04-16 17:06:23 +03:00
committed by GitHub
parent bdb9b224a8
commit 4741b0b916
11 changed files with 451 additions and 62 deletions
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10
rl_coach/architectures/head_parameters.py
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@@ -158,6 +158,16 @@ class QHeadParameters(HeadParameters):
loss_weight=loss_weight)
class ClassificationHeadParameters(HeadParameters):
def __init__(self, activation_function: str ='relu', name: str='classification_head_params',
num_output_head_copies: int = 1, rescale_gradient_from_head_by_factor: float = 1.0,
loss_weight: float = 1.0, dense_layer=None):
super().__init__(parameterized_class_name="ClassificationHead", activation_function=activation_function, name=name,
dense_layer=dense_layer, num_output_head_copies=num_output_head_copies,
rescale_gradient_from_head_by_factor=rescale_gradient_from_head_by_factor,
loss_weight=loss_weight)
class QuantileRegressionQHeadParameters(HeadParameters):
def __init__(self, activation_function: str ='relu', name: str='quantile_regression_q_head_params',
num_output_head_copies: int = 1, rescale_gradient_from_head_by_factor: float = 1.0,