Implement a reinforcement learning model which can play Tetris
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2022-07-02 03:25:28 +08:00
agent.py feat: Policy Gradient, Rewards Delay 2022-07-02 03:13:05 +08:00
enviroment.py feat: Policy Gradient, Rewards Delay 2022-07-02 03:13:05 +08:00
game.py feat: Policy Gradient, Rewards Delay 2022-07-02 03:13:05 +08:00
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train.py feat: Policy Gradient, Rewards Delay 2022-07-02 03:13:05 +08:00

TetrisRL

  • Implement a reinforcement learning model which can play Tetris

Tetris Enviroment

  • 10 actions
    • 0: don't move
    • 1: shift left 1 block
    • 2: shift left 2 block
    • 3: shift left 3 block
    • 4: shift right 1 block
    • 5: shift right 2 block
    • 6: shift right 3 block
    • 7: rotate once
    • 8: rotate twice
    • 9: rotate three times
  • return
    • pixel(10*20)
    • block_id
    • block_location(x, y)

Version 0

  • Policy Gradient Algorithm
  • Reward Delay
  • Bad Performance

TODO

  • change reward function
  • reward baseline
  • DQN