Jianye-Xu
PhD student at the Chair of Embedded Software (Informatik 11), RWTH Aachen University, Germany
Chair of Embedded Software (Informatik 11), RWTH Aachen UniversityAachen, Germany
Pinned Repositories
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SigmaRL
SigmaRL: A Sample-Efficient and Generalizable Multi-Agent Reinforcement Learning Framework for Motion Planning
p-dmpc
Prioritized Distributed Model Predictive Control for Networked Trajectory Planning
jxu.github.io
Jianye Xu's personal website
VectorizedMultiAgentSimulator
VMAS is a vectorized framework designed for efficient Multi-Agent Reinforcement Learning benchmarking. It is comprised of a vectorized 2D physics engine written in PyTorch and a set of challenging multi-robot scenarios. Additional scenarios can be implemented through a simple and modular interface.
TEAMREPO
VectorizedMultiAgentSimulator
VMAS is a vectorized differentiable simulator designed for efficient Multi-Agent Reinforcement Learning benchmarking. It is comprised of a vectorized 2D physics engine written in PyTorch and a set of challenging multi-robot scenarios. Additional scenarios can be implemented through a simple and modular interface.
Jianye-Xu's Repositories
Jianye-Xu/jxu.github.io
Jianye Xu's personal website
Jianye-Xu/VectorizedMultiAgentSimulator
VMAS is a vectorized framework designed for efficient Multi-Agent Reinforcement Learning benchmarking. It is comprised of a vectorized 2D physics engine written in PyTorch and a set of challenging multi-robot scenarios. Additional scenarios can be implemented through a simple and modular interface.