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acrobot

Use of Deep Q-Learning to build a RL Agent. Case of the Gym Acrobot-v1 environment.

Installation

Install the project environment

conda env create -f env.yml
conda activate acrobot

Training

Train the agent with

python train.py

The agent pytorch model will be saved in a file called state.pt. You can change this name and other parameter in the file train.py.

Simulation

Simulate the environment and the agent with

python test.py

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RL agent for Gym acrobot environment

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