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https://github.com/gryf/coach.git
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125c7ee38d
Main changes are detailed below: New features - * CARLA 0.7 simulator integration * Human control of the game play * Recording of human game play and storing / loading the replay buffer * Behavioral cloning agent and presets * Golden tests for several presets * Selecting between deep / shallow image embedders * Rendering through pygame (with some boost in performance) API changes - * Improved environment wrapper API * Added an evaluate flag to allow convenient evaluation of existing checkpoints * Improve frameskip definition in Gym Bug fixes - * Fixed loading of checkpoints for agents with more than one network * Fixed the N Step Q learning agent python3 compatibility
39 lines
1.3 KiB
Python
39 lines
1.3 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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from agents.actor_critic_agent import *
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from agents.agent import *
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from agents.bc_agent import *
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from agents.bootstrapped_dqn_agent import *
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from agents.clipped_ppo_agent import *
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from agents.ddpg_agent import *
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from agents.ddqn_agent import *
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from agents.dfp_agent import *
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from agents.dqn_agent import *
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from agents.categorical_dqn_agent import *
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from agents.human_agent import *
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from agents.imitation_agent import *
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from agents.mmc_agent import *
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from agents.n_step_q_agent import *
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from agents.naf_agent import *
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from agents.nec_agent import *
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from agents.pal_agent import *
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from agents.policy_gradients_agent import *
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from agents.policy_optimization_agent import *
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from agents.ppo_agent import *
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from agents.value_optimization_agent import *
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from agents.qr_dqn_agent import *
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