56 lines
2.4 KiB
Python
56 lines
2.4 KiB
Python
from __future__ import absolute_import
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from __future__ import division
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import tensorflow as tf
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class PolicyBase(object):
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"""
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Base class for policy. Mandatory methods for a policy class are:
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- :func:`act`. It's used interacting with the environment during training, \
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so exploration noise should be added in this method.
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- :func:`act_test`. Since RL usually adds additional exploration noise during training, a different method\
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for testing the policy should be defined with different exploration specification.\
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Generally, DQN uses different :math:`\epsilon` in :math:`\epsilon`-greedy and\
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DDPG removes exploration noise during test.
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- :func:`reset`. It's mainly to reset the states of the exploration random process, or if your policy has\
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some internal states that should be reset at the beginning of each new episode. Otherwise, this method\
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does nothing.
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"""
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def act(self, observation, my_feed_dict):
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"""
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Return action given observation, when interacting with the environment during training.
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:param observation: An array-like with rank the same as a single observation of the environment.
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Its "batch_size" is 1, but should not be explicitly set. This method will add the dimension
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of "batch_size" to the first dimension.
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:param my_feed_dict: A dict. Specifies placeholders such as dropout and batch_norm except observation.
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:return: A numpy array. Action given the single observation. Its "batch_size" is 1,
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but should not be explicitly set.
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"""
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raise NotImplementedError()
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def act_test(self, observation, my_feed_dict):
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"""
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Return action given observation, when interacting with the environment during test.
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:param observation: An array-like with rank the same as a single observation of the environment.
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Its "batch_size" is 1, but should not be explicitly set. This method will add the dimension
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of "batch_size" to the first dimension.
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:param my_feed_dict: A dict. Specifies placeholders such as dropout and batch_norm except observation.
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:return: A numpy array. Action given the single observation. Its "batch_size" is 1,
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but should not be explicitly set.
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"""
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raise NotImplementedError
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def reset(self):
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"""
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Reset the internal states of the policy. Does nothing by default.
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"""
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pass
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