high_level_policy_main module¶
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high_level_policy_main.
evaluate_high_level_policy
(nb_episodes_for_test=100, nb_trials=10, trained_agent_file='highlevel_weights.h5f', pretrained=False, visualize=False)¶
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high_level_policy_main.
find_good_high_level_policy
(nb_steps=25000, load_weights=False, nb_episodes_for_test=100, visualize=False, tensorboard=False, save_path='./highlevel_weights.h5f')¶
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high_level_policy_main.
high_level_policy_testing
(nb_episodes_for_test=100, trained_agent_file='highlevel_weights.h5f', pretrained=False, visualize=True)¶
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high_level_policy_main.
high_level_policy_training
(nb_steps=25000, load_weights=False, training=True, testing=True, nb_episodes_for_test=20, max_nb_steps=100, visualize=False, tensorboard=False, save_path='highlevel_weights.h5f')¶ Do RL of the high-level policy and test it.
Parameters: - nb_steps – the number of steps to perform RL
- load_weights – True if the pre-learned NN weights are loaded (for initializations of NNs)
- training – True to enable training
- testing – True to enable testing
- nb_episodes_for_test – the number of episodes for testing