Developed an Artificial Intelligence using PySC2 to train supervised agents to play the game using the concept of Reinforcement Learning (RL) and Broke down the game into manageable chunks to test RL agents on game specific tasks, and make meaningful actions in the game possible.

Reinforcement Learning Agents for SC2LE

Machine Learning App to Deep Reinforcement Learning in Starcraft 2

Starcraft II Agents using PySC2 - StarCraft II Learning Environment

This project allows to train reinforcement learning agents in pysc2 environments.

Generative-Adversarial-Imitation-Learning on PySC2

StarCraft II replay-processing pipeline.

Code to do multi agent systems research on StarCraft II. It contains methods to deal with the Raw Interface from the SC2 API, which has not been officially adapted for Python. This means that, the programmer can now access the objects at the game and the 2D original representation of the map

Example code for PySC2

A tutorial of data extraction for starcraft II replays using Deepmind's starcraft II RL environment pysc2

My pysc2 rl agent

Downloading & parsing StarCraft II replays

Parse sc2 replay files

Work on SC2 minigames with reinforcement learning

Reinforcement learning for StarcraftII

Battle experiments from my master's deep reinforcement learning research

Jaguar: A Hierarchical Deep Reinforcement Learning approach with Transfer Learning for StarCraft II

A StarCraft II bot api client library for Python 3