H.B. Jiang's repositories
robosumo-selfplay
Reproduction of self-play described in paper "Emergent Complexity via Multi-Agent Competition", adapted from PPO2 implementation in OpenAI baselines.
neurips2020-flatland-starter-kit
Forked from https://gitlab.aicrowd.com/flatland/neurips2020-flatland-starter-kit.git
baselines
OpenAI Baselines: high-quality implementations of reinforcement learning algorithms
batch-ppo
Efficient Batched Reinforcement Learning in TensorFlow
CompilerProject-2020Spring
Course Project. PKU Compiler Design. Spring, 2020.
CS294_Fall-2017_HW
Assignments for CS294-112 Fall 2017
CS294_Fall-2018_HW
Assignments for CS294-112 Fall 2018
hbjiang.github.io
白嫖一下github的https🤣
lihang-code
《统计学习方法》的代码实现
meta-mapg-code
Source code for "A Policy Gradient Algorithm for Learning to Learn in Multiagent Reinforcement Learning"
MineDojo
Building Open-Ended Embodied Agents with Internet-Scale Knowledge
Minigrid
Simple and easily configurable grid world environments for reinforcement learning
nd889
Udacity Artificial Intelligence Nanodegree
openbilibili-go-common
哔哩哔哩 bilibili 网站后台工程 源码
pomegranate
Fast, flexible and easy to use probabilistic modelling in Python.
robosumo
Code for the paper "Continuous Adaptation via Meta-Learning in Nonstationary and Competitive Environments"
spinningup
An educational resource to help anyone learn deep reinforcement learning.
StarCraft
Implementations of QMIX, VDN, COMA, QTRAN, CommNet, DyMA-CL, G2ANet on SMAC, the decentralised micromanagement scenario of StarCraft II