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"cell_type" : " markdown" ,
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"metadata" : {},
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"source" : [
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- " # Playback saved model"
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+ " ## Random action model"
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]
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},
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{
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" import pandas as pd\n " ,
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" import random\n " ,
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" \n " ,
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- " import torch\n " ,
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- " import torch.nn as nn\n " ,
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- " import torch.optim as optim\n " ,
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- " \n " ,
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- " # Use a double ended queue (deque) for memory\n " ,
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- " # When memory is full, this will replace the oldest value with the new one\n " ,
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- " from collections import deque\n " ,
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- " \n " ,
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" # Supress all warnings (e.g. deprecation warnings) for regular use\n " ,
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" import warnings\n " ,
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" \n " ,
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"metadata" : {},
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"outputs" : [],
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"source" : [
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- " MODEL_PATH = './models/'\n " ,
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- " \n " ,
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- " MODELS = {\n " ,
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- " 'ddqn':'ddqn_policy.pt',\n " ,
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- " '3dqn': '3dqn_policy.pt'\n " ,
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- " }\n " ,
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- " \n " ,
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" # Replicate runs\n " ,
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" TEST_EPISODES = 30\n " ,
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" \n " ,
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