Reaver: Modular Deep Reinforcement Learning Framework. Focused on StarCraft II. Supports Gym, Atari, and MuJoCo.
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Updated
Nov 1, 2020 - Python
Reaver: Modular Deep Reinforcement Learning Framework. Focused on StarCraft II. Supports Gym, Atari, and MuJoCo.
This is a simple implementation of DeepMind's PySC2 RL agents.
Reinforcement learning framework to accelerate research
StarCraft II / PySC2 Deep Reinforcement Learning Agents (A2C)
Startcraft II Machine Learning research with DeepMind pysc2 python library .mini-games and agents.
LLM-PySC2 is NKAI Decision Team and NUDT Decision Team's Python component of the StarCraft II LLM Decision Environment. It exposes Deepmind's PySC2 Learning Environment API as a Python LLM Environment.
Implementing reinforcement-learning algorithms for pysc2 -environment
PySC2 OpenAI Gym Environments
Curated list of pysc2 mini-games . Singleton Environmnets.Debugged by @SoyGema and mini-game authors
Data analysis of Starcraft II replays . Visualization and classification models
StarCraft II Reinforcement Learning with Pytorch - Mini Games
Convert sc2 environment to gym-atari and play some mini-games
Example code for PySC2
Applying the DQN-Agent from keras-rl to Starcraft 2 Learning Environment and modding it to to use the Rainbow-DQN algorithms.
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
Mini-games consisting of different scenarios in sc2 for use in training and testing StarCraft 2 bots
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