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RL in Large Discrete Action Spaces - Wolpertinger Agent (#394)

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* Currently this is specific to the case of discretizing a continuous action space. Can easily be adapted to other case by feeding the kNN otherwise, and removing the usage of a discretizing output action filter
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Gal Leibovich
2019-09-08 12:53:49 +03:00
committed by GitHub
parent fc50398544
commit 138ced23ba
46 changed files with 1193 additions and 51 deletions
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rl_coach/exploration_policies/exploration_policy.py
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@@ -115,5 +115,8 @@ class ContinuousActionExplorationPolicy(ExplorationPolicy):
"""
:param action_space: the action space used by the environment
"""
assert isinstance(action_space, BoxActionSpace) or isinstance(action_space, GoalsSpace)
assert isinstance(action_space, BoxActionSpace) or \
(hasattr(action_space, 'filtered_action_space') and
isinstance(action_space.filtered_action_space, BoxActionSpace)) or \
isinstance(action_space, GoalsSpace)
super().__init__(action_space)