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keras-only-RL

Implementating Reinforcement Learning from A to Z using keras only.

How to run

For example: Run Atari Breakout with D3QN Agent

sh atari_breakout_run.sh --double=True --dueling=True

demo

Help

sh atari_breakout_run.sh -h
usage: main.py [-h] [--e E] [--double D] [--dueling B]

Some hyperparameters

optional arguments:
  -h, --help   show this help message and exit
  --e E        Total episodes
  --double D   Enable Double DQN
  --dueling B  Enable Dueling DQN

To the Rainbow

Technique Problem How to solve it
DQN Non-stationary targets makes learning unstable Fixed Q-targets
Correlation between samples makes W biased Replay Memory
Double ~ Maximum estimator raises over-estimation Using double estimators
Dueling ~ Some state may have inherently low value Q(s, a) = V(s) + A(s, a)

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implementing RLs using keras only

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