import?numpy?as?np
import?math
from?keras.initializations?import?normal?identity
from?keras.models?import?model_from_json
from?keras.models?import?Sequential?Model
from?keras.engine.training?import?collect_trainable_weights
from?keras.layers?import?Dense?Flatten?Input?merge?Lambda
from?keras.optimizers?import?Adam
import?tensorflow?as?tf
import?keras.backend?as?K

HIDDEN1_UNITS?=?300
HIDDEN2_UNITS?=?600

class?ActorNetwork（object）:
????def?__init__（self?sess?state_size?action_size?BATCH_SIZE?TAU?LEARNING_RATE）:
????????self.sess?=?sess
????????self.BATCH_SIZE?=?BATCH_SIZE
????????self.TAU?=?TAU
????????self.LEARNING_RATE?=?LEARNING_RATE

????????K.set_session（sess）

????????#Now?create?the?model
????????self.model??self.weights?self.state?=?self.create_actor_network（state_size?action_size）???
????????self.target_model?self.target_weights?self.target_state?=?self.create_actor_network（state_size?action_size）?
????????self.action_gradient?=?tf.placeholder（tf.float32[None?action_size]）
????????self.params_grad?=?tf.gradients（self.model.output?self.weights?-self.action_gradient）
????????grads?=?zip（self.params_grad?self.weights）
????????self.optimize?=?tf.train.AdamOptimizer（LEARNING_RATE）.apply_gradients（grads）
????????self.sess.run（tf.initialize_all_variables（））

????def?train（self?states?action_grads）:
????????self.sess.run（self.optimize?feed_dict={
????????????self.state:?states
????????????self.action_gradient:?action_grads
????????}）

????def?target_train（self）:
????????actor_weights?=?self.model.get_weights（）
????????actor_target_weights?=?self.target_model.get_weights（）
????????for?i?in?xrange（len（actor_weights））:
????????????actor_target_weights[i]?=?self.TAU?*?actor_weights[i]?+?（1?-?self.TAU）*?actor_target_weights[i]
????????self.target_model.set_weights（actor_target_weights）

????def?create_actor_network（self?state_sizeaction_dim）:
????????print（“Now?we?build?the?model“）
????????S?=?Input（shape=[state_size]）???
????????h0?=?Dense（HIDDEN1_UNITS?activation=‘relu‘）（S）
????????h1?=?Dense（HIDDEN2_UNITS?activation=‘relu‘）（h0）
????????Steering?=?Dense（1activation=‘tanh‘init=lambda?shape?name:?normal（shape?scale=1e-4?name=name））（h1）??
????????Acceleration?=?Dense（1activation=‘sigmoid‘init=lambda?shape?name:?normal（shape?scale=1e-4?name=name））（h1）???
????????Brake?=?Dense（1activation=‘sigmoid‘init=lambda?shape?name:?normal（shape?scale=1e-4?name=name））（h1）?
????????V?=?merge（[SteeringAccelerationBrake]mode=‘concat‘）??????????
????????model?=?Model（input=Soutput=V）
????????return?model?model.trainable_weights?S

?屬性????????????大小?????日期????時間???名稱
-----------?---------??----------?-----??----

?????文件?????779336??2016-10-11?22:25??book_code_01\chapter_10\DDPG-Keras-Torcs-master\actormodel.h5

?????文件???????2682??2016-10-11?22:25??book_code_01\chapter_10\DDPG-Keras-Torcs-master\actormodel.json

?????文件???????2606??2016-10-11?22:25??book_code_01\chapter_10\DDPG-Keras-Torcs-master\ActorNetwork.py

?????文件????????206??2016-10-11?22:25??book_code_01\chapter_10\DDPG-Keras-Torcs-master\autostart.sh

?????文件????2232192??2016-10-11?22:25??book_code_01\chapter_10\DDPG-Keras-Torcs-master\criticmodel.h5

?????文件???????2916??2016-10-11?22:25??book_code_01\chapter_10\DDPG-Keras-Torcs-master\criticmodel.json

?????文件???????2438??2016-10-11?22:25??book_code_01\chapter_10\DDPG-Keras-Torcs-master\CriticNetwork.py

?????文件???????5962??2016-10-11?22:25??book_code_01\chapter_10\DDPG-Keras-Torcs-master\ddpg.py

?????文件???12208354??2016-10-11?22:25??book_code_01\chapter_10\DDPG-Keras-Torcs-master\fast.gif

?????文件??????11140??2016-10-11?22:25??book_code_01\chapter_10\DDPG-Keras-Torcs-master\gym_torcs.py

?????文件????????159??2016-10-11?22:25??book_code_01\chapter_10\DDPG-Keras-Torcs-master\OU.py

?????文件????????614??2016-10-11?22:25??book_code_01\chapter_10\DDPG-Keras-Torcs-master\README.md

?????文件???????1119??2016-10-11?22:25??book_code_01\chapter_10\DDPG-Keras-Torcs-master\ReplayBuffer.py

?????文件??????23823??2016-10-11?22:25??book_code_01\chapter_10\DDPG-Keras-Torcs-master\snakeoil3_gym.py

?????文件???????3062??2018-04-11?14:19??book_code_01\chapter_2\HuskyPractice-master\CMakeLists.txt

?????文件????????437??2018-04-11?14:19??book_code_01\chapter_2\HuskyPractice-master\include\husky_high_level_controller\husky_controller.hpp

?????文件????????471??2018-04-11?14:19??book_code_01\chapter_2\HuskyPractice-master\launch\high_controller.launch

?????文件???????2808??2018-04-11?14:19??book_code_01\chapter_2\HuskyPractice-master\package.xml

?????文件????????129??2018-04-11?14:19??book_code_01\chapter_2\HuskyPractice-master\README.md

?????文件???????1059??2018-04-11?14:19??book_code_01\chapter_2\HuskyPractice-master\src\husky_controller.cpp

?????文件????????403??2018-04-11?14:19??book_code_01\chapter_2\HuskyPractice-master\src\husky_high_level_controller_node.cpp

?????文件?????????30??2018-07-31?17:01??book_code_01\chapter_3\NDT_PCL_demo\.idea\.name

?????文件???????1775??2018-07-31?17:01??book_code_01\chapter_3\NDT_PCL_demo\.idea\codestyles\Project.xml

?????文件????????137??2018-07-31?17:01??book_code_01\chapter_3\NDT_PCL_demo\.idea\misc.xml

?????文件????????276??2018-07-31?17:01??book_code_01\chapter_3\NDT_PCL_demo\.idea\modules.xml

?????文件?????????97??2018-07-31?17:01??book_code_01\chapter_3\NDT_PCL_demo\.idea\NDT_PCL_demo.iml

?????文件??????13412??2018-07-31?19:18??book_code_01\chapter_3\NDT_PCL_demo\.idea\workspace.xml

?????文件????3620143??2018-07-31?17:39??book_code_01\chapter_3\NDT_PCL_demo\build\cloud3.pcd

?????文件??????47246??2018-07-31?17:33??book_code_01\chapter_3\NDT_PCL_demo\build\CMakeCache.txt

?????文件???????2002??2018-07-31?17:33??book_code_01\chapter_3\NDT_PCL_demo\build\CMakeFiles\3.5.1\CMakeCCompiler.cmake

............此處省略94個文件信息