Hill Climbing methods
Description
In this repo I explore the Hill Climbing improvements like adaptative nopise scaling and cross-entropy to use them to solve the enviroment CartPole-v0 from OpenAI-GYM.
Usage
The RL algorithm is located under the "ce_w_ans_agent.py" file and to test it working over the gym environment you shuld run the jupyter notebook OpenAI_Gym_CartPole-v0.ipynb in which you can train the agent from scratch or coment the training fase and load the weigths to test it.
Installation
To use this code you need to install the following packages:
- gym
- numpy
- jupiyter
- matplotlib
License
GNU General Public License v3.0