PyDiffGame is a Python implementation of a Nash Equilibrium solution to Differential Games, based on a reduction of Game Hamilton-Bellman-Jacobi (GHJB) equations to Game Algebraic and Differential Riccati equations, associated with Multi-Objective Dynamical Control Systems

Python code for solving partial differential equations (PDEs) using deep learning. Specifically, we provide implementations for solving the following PDEs

Continuous-Time/State/Action Fitted Value Iteration via Hamilton-Jacobi-Bellman (HJB)

A range of Hamilton–Jacobi–Bellman (HJB) solvers. Solve optimisation problems with dynamic programming.

A GPU-accelerated toolbox for hyperbolic PDEs in a weaker (viscosity) sense. It leverages the integral to the solution of the conservation of momentum problem (being equivalent to the derivative of Hamilton-Jacobi equations) in one spatial dimension. We resolve such hyperbolic differential equations using wave-front propagating schemes on a spat…

A parallel solver for first-order static Hamilton-Jacobi PDEs

Risk-sensitive asset management simulation in Matlab.

🚀✈️🎯 Fork of HJReachability's helperOC library for the MATLAB development part of my Master's Thesis on Hamilton Jacobi Reachability in collaboration with Georgia Tech's School of Aerospace Engineering.

Repository for the code of the "Dynamic Programming and Optimal Control" (DPOC) lecture at the "Institute for Dynamic Systems and Control" at ETH Zurich.

En este repositorio pueden encontrarse los códigos utilizados para realizar el trabajo de tesis de maestría.