pokemon-deep-learning
An openAI gym project for pokemon involving deep q learning. Made by myself, Sam Little, and Layton Webber.
This code captures games played online, interprets them, updates a RNN to learn from them, and implements and evaluates them against a random agent.
Requires a locally hosted node.js Pokemon Showdown server and poke-env.
Gym can be installed with ‘pip install -e agent_vs_agent’.
Program can be run with ‘python3 main.py’.
