Automated Machine Learning with scikit-learn
OpenDILab Decision AI Engine. The Most Comprehensive Reinforcement Learning Framework B.P.
This is the official implementation of Multi-Agent PPO (MAPPO).
Fine-tuned MARL algorithms on SMAC (100% win rates on most scenarios)
Unofficial open-source OpenGL/SDL2 reimplementation of Sid Meier's Alpha Centauri ( + Alien Crossfire )
[AAAI 2023] Official PyTorch implementation of paper "ACE: Cooperative Multi-agent Q-learning with Bidirectional Action-Dependency".
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.
StarCraft II Multi Agent Challenge : QMIX, COMA, LIIR, QTRAN, Central V, ROMA, RODE, DOP, Graph MIX
Multi-agent PPO with noise (97% win rates on Hard scenarios of SMAC)
[ICML 2021] DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning
Bayesian Optimization for Categorical and Continuous Inputs
Continual Multi-agent Reinforcement Learning in Dynamic Environments
Anti-Cheat Detection for Game Streaming
Clean, documented implementations of PPO-based algorithms for cooperative multi-agent reinforcement learning, focusing on SMAC environments. Features MLP and RNN-based MAPPO with various normalization techniques.
[JMLR 2023] A Unified Framework for Factorizing Distributional Value Functions for Multi-Agent Reinforcement Learning
An automated data augmentation tool in Python
This is the official implementation of [AAAI'25 Oral] accepted paper: Bridging Training and Execution via Dynamic Directed Graph-Based Communication in Cooperative Multi-Agent Systems.
In this project, we focus on different ways to optimize a machine learning model parameters.
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