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paia_arkanoid_hw's Introduction

基於遊戲的機器學習入門第一次作業

成果展示

影片

Untitled.video.3.mp4

模型訓練

資料收集

  1. 執行data_collect.py,使用ml_play_template.py的算法打磚塊
  2. ml_play_template.py充滿了各種random,收集資料時可以重複玩某一關直到通關
  3. 收集到的資料會存成.pickle,會儲存磚塊、球、盤子的位置、執行的動作等資料(詳見ml_play_template.py)

資料清理與轉換

  1. train_data_generator.py會使用tool.data_clean.data_compare()來確保同樣的情況,都記錄相同的動作
  2. 會以越接近結尾的資料其紀錄的動作為準
  3. 清理完畢後,會將所儲存的資料的位置全部標示到np_array上(使用tool.data_generator.get_graph()),並以.pickle儲存

使用pytorch CNN做訓練

  1. 由於關卡是固定的,過擬和似乎變成一個好選擇???
  2. 礙於時間(其實是懶),我沒有蒐集第18和24關的資料,如果有蒐集應該也能通關

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