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README.md

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-# policy_entropy
-Source code for the numerical experiments presented in the paper "Analyzing Policy Entropy of Reinforcement Learning Agents for Personalization Tasks".
+# Policy Entropy of RL Agents
+
+This repository contains the source code for the numerical experiments presented in the paper "Analyzing Policy Entropy of Reinforcement Learning Agents for Personalization Tasks".
+
+## How to Use
+
+### Installation
+Install the requirements via `pip install -r requirements.txt`.
+
+### Run Experiments
+Run the experiments via `python -m run_experiment -c config`, where `config` is a configuration file in `./configs/` directory.
+The available values are `{config_mnist, config_cifar10, config_spotify, config_recogym, config_personalization}`, which could be specified to recreate each of the presented numerical experiments.
+Optionally, a custom experiment can be set up by changing the `./configs/config.yml` file.
+
+### Load Experiments
+All previously performed experiments are stored in `./data/` directory and can be recreated by loading via `python -m run_experiment -l exp_name`, where `exp_name` is the name of the experiment as it is saved in `./data/`.
+
+
+## File Structure
+* `run_experiment.py` --- set up and run the experiment
+* `agent.py` --- set up selected RL agents
+* `environment.py` --- create the specified environment
+* `environments/` --- data required to set up various environments
+* `configs/` --- configuration files for the experiments
+* `data/` --- store data from previously run experiments
+* `images/` --- plots of various results from experiments
+* `visualization.py` --- save/load the experiment data, plot the results
+
+## License
+This project is licensed under the MIT License.
+
+
+