Arthur Juliani awjuliani

## Q-Net Learning Clean.ipynb

      
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                awjuliani
                / Q-Net Learning Clean.ipynb
            
            
              Created
              August 25, 2016 20:30
            
              
                Basic Q-Learning algorithm using Tensorflow
              
          
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## InfoGAN-Tutorial.ipynb

      
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                awjuliani
                / InfoGAN-Tutorial.ipynb
            
            
              Created
              October 22, 2016 02:10
            
              
                An implementation of InfoGAN.
              
          
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## Deep-Recurrent-Q-Network.ipynb

      
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                awjuliani
                / Deep-Recurrent-Q-Network.ipynb
            
            
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              July 18, 2023 19:18
            
              
                An implementation of a Deep Recurrent Q-Network in Tensorflow.
              
          
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## SimplePolicy.ipynb

      
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                awjuliani
                / SimplePolicy.ipynb
            
            
              Created
              September 11, 2016 00:20
            
              
                Policy gradient method for solving n-armed bandit problems.
              
          
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## Q-Table Learning-Clean.ipynb

      
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                awjuliani
                / Q-Table Learning-Clean.ipynb
            
            
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              October 25, 2022 07:57
            
              
                Q-Table learning in OpenAI grid world.
              
          
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## ContextualPolicy.ipynb

      
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                awjuliani
                / ContextualPolicy.ipynb
            
            
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              October 11, 2022 21:27
            
              
                A Policy-Gradient algorithm that solves Contextual Bandit problems.
              
          
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## Q-Exploration.ipynb

      
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                awjuliani
                / Q-Exploration.ipynb
            
            
              Created
              November 14, 2016 21:57
            
          
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## train.py
class AC_Network():
    def __init__(self,s_size,a_size,scope,trainer):
        ....
        ....
        ....
        if scope != 'global':
            self.actions = tf.placeholder(shape=[None],dtype=tf.int32)
            self.actions_onehot = tf.one_hot(self.actions,a_size,dtype=tf.float32)
            self.target_v = tf.placeholder(shape=[None],dtype=tf.float32)
            self.advantages = tf.placeholder(shape=[None],dtype=tf.float32)

## softmax.ipynb

      
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                awjuliani
                / softmax.ipynb
            
            
              Last active
              September 14, 2021 20:52
            
              
                A simple ipython notebook that walks through the creation of a softmax regression model using MNIST dataset.
              
          
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## rl-tutorial-3.ipynb

      
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                awjuliani
                / rl-tutorial-3.ipynb
            
            
              Last active
              March 24, 2021 07:38
            
              
                Reinforcement Learning Tutorial in Tensorflow: Model-based RL
              
          
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	class AC_Network():
	def __init__(self,s_size,a_size,scope,trainer):
	....
	....
	....
	if scope != 'global':
	self.actions = tf.placeholder(shape=[None],dtype=tf.int32)
	self.actions_onehot = tf.one_hot(self.actions,a_size,dtype=tf.float32)
	self.target_v = tf.placeholder(shape=[None],dtype=tf.float32)
	self.advantages = tf.placeholder(shape=[None],dtype=tf.float32)