leap-c
provides tools for learning optimal control policies using Imitation learning (IL) and Reinforcement Learning (RL) to enhance Model Predictive Control (MPC) algorithms. It is built on top of CasADi, acados and PyTorch.
leap-c
can be set up up by following the installation guide.
Please see the Getting started section or the examples folder.
Open a new thread or browse the existing ones on the GitHub discussions page.