Liangyawei Kuang's Projects
One thing that is really hard to be believed is that the Algorithm course only covers the theoretical part without implementation. Due to this case, this code set is to help you have a better understanding of the algorithms by programming. The languages used are only C++ and Java. Have fun!
"Being alchemy is certainly not a shame, not wanting to work on advancing to chemistry is a shame!" -- by Eric Xing
Implementation of GNN and GCN in Multi-Agent Systems.
We always blow our university, HKUST, as one of the top 30 or 40 universities in the world. But we don't even have an official reference letter template like many other good universities. Here and now we have it! The unofficial template!
My Implementation of algorithms on basic RL, advanced RL, and MARL.
Config files for my GitHub profile.
This is Liangyawei Kuang's personal academic webpage.
Implementation of "Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments".
Multi-Agent Pathfinding is about the problem that agents will be able to follow these paths concurrently without colliding with each other.
The research area now known as multi-agent systems (MAS) was initially called “distributed AI” (DAI). MAS research is to study systems that consist of a group of agents that can potentially interact with each other. Here is a handful of resources that may be helpful to you at the beginning of your research work in this area.
This 30-week course is a combination of some robotics, SLAM, reinforcement learning, and game theory topics, which are related to MRS.
There are not too many fancy SOTA algorithms in OS, but we can still play some of them.
Implementation of "QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning".
My superficial research notes about Reinforcement Learning.
Statistical learning refers to a set of tools for modeling and understanding complex datasets. It is a recently developed area in statistics, and blends with parallel developments in computer science, and in particular machine learning.