Wrappers for reinforcement learning algorithms (i.e. stable baselines 3, RLlib) to work with pyRDDLGym.
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Updated
Nov 4, 2024 - Python
Wrappers for reinforcement learning algorithms (i.e. stable baselines 3, RLlib) to work with pyRDDLGym.
Gurobi compilation of RDDL description files to mixed-integer programs, and optimization tools.
Docker files for connecting the PROST planner with pyRDDLGym.
Sidney's Technical Blog
Sketches of model-based control ideas for gym classic control
JAX compilation of RDDL description files, and a differentiable planner in JAX.
[NeurIPS 2024] Input-to-State Stable Coupled Oscillator Networks for Closed-form Model-based Control in Latent Space
For the consolidation of my personal model predictive control (MPC) library. Example cases also given.
We compare model-free and model-based methods in the context of battery control.
Model-based Calibration of Multiple Injections for a CI engine
PyTorch implementation of "Learning Stable Deep Dynamics Models" (https://papers.nips.cc/paper/9292-learning-stable-deep-dynamics-models), with extensions to controlled dynamical systems.
Height Control and Optimal Torque Planning for Jumping with Wheeled-Bipedal Robots
Model-based Control using Koopman Operators
An open-source systems and controls toolbox for Python3
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