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License: MIT License

Jupyter Notebook 99.88% Python 0.12%
ppo proximal-policy-optimization policy-gradient deep-reinforcement-learning reinforcement-learning pytorch openai-gym policy-optimization atari-pong

openai-gym-pongdeterministic-v4-ppo's Introduction

OpenAI-Gym-PongDeterministic-v4-PPO

Pong-v0 Maximize your score in the Atari 2600 game Pong. In this environment, the observation is an RGB image of the screen, which is an array of shape (210, 160, 3) Each action is repeatedly performed for a duration of kk frames, where kk is uniformly sampled from {2, 3, 4}{2,3,4}.

Installation

$ pip install gym\[atari\]
$ pip install 'gym[atari]'

Arguments

gym.make('PongDeterministic-v4')

Instructions

$ git clone https://github.com/bmaxdk/OpenAI-Gym-PongDeterministic-v4-PPO
$ cd OpenAI-Gym-PongDeterministic-v4-PPO

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