In this PR, I wanted to solve issue #25 by creating a CSV file to list and also help the brand property matching process. This PR including:
Compile a list of all brand names and operator names from the name-suggestion-index as a CSV with the columns id, display_name, and wiki_data in tmp folder. Deadline: 05.01.2022
Create a PySpark UDF similar to the ones in the osm
Code from the paper "Effective Diversity in Population Based Reinforcement Learning", presented as a spotlight at NeurIPS 2020. This is the Evolution Strategies implementation, but of course the method can be used for gradient based RL algorithms (e.g. TD3).
Create a small project that demonstrates the abilities of the NEAT algorithm. It could be a game or a simple function-approximating application (ex. modeling the trigonometric functions using a neural network and a relatively large data set).
