update

contents/10_A3C/A3C_RNN.py

@@ -3,7 +3,7 @@
 
 The Pendulum example.
 
-View more on [莫烦Python] : https://morvanzhou.github.io/tutorials/
+View more on my tutorial page: https://morvanzhou.github.io/tutorials/
 
 Using:
 tensorflow 1.0

contents/10_A3C/A3C_continuous_action.py

@@ -3,7 +3,7 @@
 
 The Pendulum example.
 
-View more on [莫烦Python] : https://morvanzhou.github.io/tutorials/
+View more on my tutorial page: https://morvanzhou.github.io/tutorials/
 
 Using:
 tensorflow 1.0

contents/10_A3C/A3C_discrete_action.py

@@ -3,7 +3,7 @@
 
 The Cartpole example.
 
-View more on [莫烦Python] : https://morvanzhou.github.io/tutorials/
+View more on my tutorial page: https://morvanzhou.github.io/tutorials/
 
 Using:
 tensorflow 1.0

contents/11_Dyna_Q/RL_brain.py

@@ -2,7 +2,7 @@
 This part of code is the Dyna-Q learning brain, which is a brain of the agent.
 All decisions and learning processes are made in here.
 
-View more on 莫烦Python: https://morvanzhou.github.io/tutorials/
+View more on my tutorial page: https://morvanzhou.github.io/tutorials/
 """
 
 import numpy as np

contents/11_Dyna_Q/maze_env.py

@@ -8,7 +8,7 @@
 
 This script is the environment part of this example. The RL is in RL_brain.py.
 
-View more on 莫烦Python: https://morvanzhou.github.io/tutorials/
+View more on my tutorial page: https://morvanzhou.github.io/tutorials/
 """
 
 

contents/11_Dyna_Q/run_this.py

@@ -9,7 +9,7 @@
 This script is the main part which controls the update method of this example.
 The RL is in RL_brain.py.
 
-View more on 莫烦Python: https://morvanzhou.github.io/tutorials/
+View more on my tutorial page: https://morvanzhou.github.io/tutorials/
 """
 
 from maze_env import Maze

contents/1_command_line_reinforcement_learning/treasure_on_right.py

@@ -3,7 +3,7 @@
 An agent "o" is on the left of a 1 dimensional world, the treasure is on the rightmost location.
 Run this program and to see how the agent will improve its strategy of finding the treasure.
 
-View more on 莫烦Python: https://morvanzhou.github.io/tutorials/
+View more on my tutorial page: https://morvanzhou.github.io/tutorials/
 """
 
 import numpy as np

contents/2_Q_Learning_maze/RL_brain.py

@@ -2,7 +2,7 @@
 This part of code is the Q learning brain, which is a brain of the agent.
 All decisions are made in here.
 
-View more on 莫烦Python: https://morvanzhou.github.io/tutorials/
+View more on my tutorial page: https://morvanzhou.github.io/tutorials/
 """
 
 import numpy as np

contents/2_Q_Learning_maze/maze_env.py

@@ -8,7 +8,7 @@
 
 This script is the environment part of this example. The RL is in RL_brain.py.
 
-View more on 莫烦Python: https://morvanzhou.github.io/tutorials/
+View more on my tutorial page: https://morvanzhou.github.io/tutorials/
 """
 
 

contents/2_Q_Learning_maze/run_this.py

@@ -9,7 +9,7 @@
 This script is the main part which controls the update method of this example.
 The RL is in RL_brain.py.
 
-View more on 莫烦Python: https://morvanzhou.github.io/tutorials/
+View more on my tutorial page: https://morvanzhou.github.io/tutorials/
 """
 
 from maze_env import Maze

contents/3_Sarsa_maze/RL_brain.py

@@ -2,7 +2,7 @@
 This part of code is the Q learning brain, which is a brain of the agent.
 All decisions are made in here.
 
-View more on 莫烦Python: https://morvanzhou.github.io/tutorials/
+View more on my tutorial page: https://morvanzhou.github.io/tutorials/
 """
 
 import numpy as np

contents/3_Sarsa_maze/maze_env.py

@@ -9,7 +9,7 @@
 This script is the environment part of this example.
 The RL is in RL_brain.py.
 
-View more on 莫烦Python: https://morvanzhou.github.io/tutorials/
+View more on my tutorial page: https://morvanzhou.github.io/tutorials/
 """
 
 

contents/4_Sarsa_lambda_maze/RL_brain.py

@@ -2,7 +2,7 @@
 This part of code is the Q learning brain, which is a brain of the agent.
 All decisions are made in here.
 
-View more on 莫烦Python: https://morvanzhou.github.io/tutorials/
+View more on my tutorial page: https://morvanzhou.github.io/tutorials/
 """
 
 import numpy as np

contents/4_Sarsa_lambda_maze/maze_env.py

@@ -9,7 +9,7 @@
 This script is the environment part of this example.
 The RL is in RL_brain.py.
 
-View more on 莫烦Python: https://morvanzhou.github.io/tutorials/
+View more on my tutorial page: https://morvanzhou.github.io/tutorials/
 """
 
 

contents/5.1_Double_DQN/RL_brain.py

@@ -1,7 +1,7 @@
 """
 The double DQN based on this paper: https://arxiv.org/abs/1509.06461
 
-View more on 莫烦Python: https://morvanzhou.github.io/tutorials/
+View more on my tutorial page: https://morvanzhou.github.io/tutorials/
 
 Using:
 Tensorflow: 1.0

contents/5.1_Double_DQN/run_Pendulum.py

@@ -2,7 +2,7 @@
 Double DQN & Natural DQN comparison,
 The Pendulum example.
 
-View more on 莫烦Python: https://morvanzhou.github.io/tutorials/
+View more on my tutorial page: https://morvanzhou.github.io/tutorials/
 
 Using:
 Tensorflow: 1.0

contents/5.2_Prioritized_Replay_DQN/RL_brain.py

@@ -1,7 +1,7 @@
 """
 The DQN improvement: Prioritized Experience Replay (based on https://arxiv.org/abs/1511.05952)
 
-View more on 莫烦Python: https://morvanzhou.github.io/tutorials/
+View more on my tutorial page: https://morvanzhou.github.io/tutorials/
 
 Using:
 Tensorflow: 1.0

contents/5.2_Prioritized_Replay_DQN/run_MountainCar.py

@@ -1,7 +1,7 @@
 """
 The DQN improvement: Prioritized Experience Replay (based on https://arxiv.org/abs/1511.05952)
 
-View more on 莫烦Python: https://morvanzhou.github.io/tutorials/
+View more on my tutorial page: https://morvanzhou.github.io/tutorials/
 
 Using:
 Tensorflow: 1.0

contents/5.3_Dueling_DQN/RL_brain.py

@@ -1,7 +1,7 @@
 """
 The Dueling DQN based on this paper: https://arxiv.org/abs/1511.06581
 
-View more on 莫烦Python: https://morvanzhou.github.io/tutorials/
+View more on my tutorial page: https://morvanzhou.github.io/tutorials/
 
 Using:
 Tensorflow: 1.0

contents/5.3_Dueling_DQN/run_Pendulum.py

@@ -1,7 +1,7 @@
 """
 Dueling DQN & Natural DQN comparison
 
-View more on 莫烦Python: https://morvanzhou.github.io/tutorials/
+View more on my tutorial page: https://morvanzhou.github.io/tutorials/
 
 Using:
 Tensorflow: 1.0

contents/5_Deep_Q_Network/DQN_modified.py

@@ -3,7 +3,7 @@
 
 view the tensorboard picture about this DQN structure on: https://morvanzhou.github.io/tutorials/machine-learning/reinforcement-learning/4-3-DQN3/#modification
 
-View more on 莫烦Python: https://morvanzhou.github.io/tutorials/
+View more on my tutorial page: https://morvanzhou.github.io/tutorials/
 
 Using:
 Tensorflow: 1.0

contents/5_Deep_Q_Network/RL_brain.py

@@ -3,7 +3,7 @@
 All decisions are made in here.
 Using Tensorflow to build the neural network.
 
-View more on 莫烦Python: https://morvanzhou.github.io/tutorials/
+View more on my tutorial page: https://morvanzhou.github.io/tutorials/
 
 Using:
 Tensorflow: 1.0

contents/5_Deep_Q_Network/maze_env.py

@@ -9,7 +9,7 @@
 This script is the environment part of this example.
 The RL is in RL_brain.py.
 
-View more on 莫烦Python: https://morvanzhou.github.io/tutorials/
+View more on my tutorial page: https://morvanzhou.github.io/tutorials/
 """
 
 

contents/6_OpenAI_gym/RL_brain.py

@@ -3,7 +3,7 @@
 All decisions are made in here.
 Using Tensorflow to build the neural network.
 
-View more on 莫烦Python: https://morvanzhou.github.io/tutorials/
+View more on my tutorial page: https://morvanzhou.github.io/tutorials/
 
 Using:
 Tensorflow: 1.0

contents/7_Policy_gradient_softmax/RL_brain.py

@@ -4,7 +4,7 @@
 
 Policy Gradient, Reinforcement Learning.
 
-View more on 莫烦Python: https://morvanzhou.github.io/tutorials/
+View more on my tutorial page: https://morvanzhou.github.io/tutorials/
 
 Using:
 Tensorflow: 1.0

contents/7_Policy_gradient_softmax/run_CartPole.py

@@ -3,7 +3,7 @@
 
 The cart pole example
 
-View more on [莫烦Python] : https://morvanzhou.github.io/tutorials/
+View more on my tutorial page: https://morvanzhou.github.io/tutorials/
 
 Using:
 Tensorflow: 1.0

contents/7_Policy_gradient_softmax/run_MountainCar.py

@@ -3,7 +3,7 @@
 
 The cart pole example
 
-View more on [莫烦Python] : https://morvanzhou.github.io/tutorials/
+View more on my tutorial page: https://morvanzhou.github.io/tutorials/
 
 Using:
 Tensorflow: 1.0

contents/8_Actor_Critic_Advantage/AC_CartPole.py

@@ -3,7 +3,7 @@
 
 The cart pole example. Policy is oscillated.
 
-View more on [莫烦Python] : https://morvanzhou.github.io/tutorials/
+View more on my tutorial page: https://morvanzhou.github.io/tutorials/
 
 Using:
 tensorflow 1.0

contents/8_Actor_Critic_Advantage/AC_continue_Pendulum.py

@@ -5,7 +5,7 @@
 
 Cannot converge!!! oscillate!!!
 
-View more on [莫烦Python] : https://morvanzhou.github.io/tutorials/
+View more on my tutorial page: https://morvanzhou.github.io/tutorials/
 
 Using:
 tensorflow 1.0

contents/9_Deep_Deterministic_Policy_Gradient_DDPG/DDPG.py

@@ -3,7 +3,7 @@
 DDPG is Actor Critic based algorithm.
 Pendulum example.
 
-View more on [莫烦Python] : https://morvanzhou.github.io/tutorials/
+View more on my tutorial page: https://morvanzhou.github.io/tutorials/
 
 Using:
 tensorflow 1.0