RL Final Project

We tested different algorithms on different gym environments (cliff walking, pendulum, and mountain car continuous).

Getting started

To start with, you can run the following command to create an anaconda environment and install required dependencies.

pip install -r requirements.txt

Instructions

In Linux system, you can use the scripts in ./scripts to search adquate hyperparameters. Example:

bash scripts/MountainCarDDPGSearch.sh

To train an agent for specific target task, you may enter the target task folder, and run the following command. Example:

python Pendulum/DDPG.py --max_episode=10000 --tau=0.005 --exploration_noise=0.1

You may also specify the seed value by adding --seedand --random_seed flags after the command above. You may customize other flags for convenience as well.

Test your models

After trained a model, you can test it. Example:

python Pendulum/DDPG.py --mode=test --record_test=True --tau=0.005 --exploration_noise=0.1