A component of the SciML scientific machine learning ecosystem for optimal control
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Updated
Nov 30, 2020 - Julia
A component of the SciML scientific machine learning ecosystem for optimal control
Julia interface to CasADi via PyCall
A package for solving Differential Dynamic Programming and trajectory optimization problems.
Algorithm and model experiments for robot motion planning. Implemented in Julia.
Data Processing and Simulation Tools for Networked SIR+
A Julia package for constrained trajectory optimization using direct methods.
Optimization, optimal control and optimal transport tools for spatial and temporal data mining. Part of Mathepia.jl
Optimal epidemic control by deep learning techniques
Optimization, optimal control and optimal transport tools for spatial and temporal data mining. Part of Mathepia.jl
SecondOrderPOC.jl - Formulating and solving optimal control problems in Julia.
Optimal Importance Sampling for Diffusion processes applied to ISOKANN.
A tiny quantum optimal control library.
An optional control algorithm, iterative Linear Quadratic Regulator, implementation using Julia.
A toolbox for controller design using the System Level Synthesis (SLS) methodology
A tool to solve optimal control problem
Neural ODEs as Feedback Policies for Nonlinear Optimal Control (IFAC 2023) https://doi.org/10.1016/j.ifacol.2023.10.1248
A Stochastic Primal-Dual Proximal Splitting Method for Risk-Averse Optimal Control of PDEs
Adaptive importance sampling modification to MPPI
An unofficial interface from Julia to Acados going through Casadi using PyCall
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