Iterative Linear Quadratic Regulator with auto-differentiatiable dynamics models
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Updated
Jun 21, 2022 - Python
Iterative Linear Quadratic Regulator with auto-differentiatiable dynamics models
iterative Linear Quadratic Regulator with constraints.
A toolbox for trajectory optimization of dynamical systems
Tensorflow implementation of the asynchronous advantage actor-critic (a3c) reinforcement learning algorithm for continuous action space
Open AI Gym - Pendulum-v1 reinforcement learning (DQN, SAC)
ICalLibrary - Fast, yet simple, iCalendar reader with excellent recurrence support in Python
Code for FLEX, a fast, adaptive and flexible model-based reinforcement learning exploration algorithm.
Train agents to balance an inverting pendulum
3D pendulum simulation from first principals
Tensorflow implementation of reinforcement learning (PG, A2C, DQN, DDPG, PPO, HER, SAC)
Fully customizable/interactable pendulum simulation with 3 PDE methods and an ability to use none of them. Comes with a GUI; Is easily generalizable. PDE-s derived from MatLab.
A simple Python program, which allows the automatic symbolic creation of the Lagrange equations for pendulums and similar objects. Furthermore a numerical solver is used in order to approximate the solutions.
Yet another time tracker
Simulations of simple and double pendulums
Double Pendulum Simulation showing chaos emerging from slightly different initial conditions.
Inverted pendulum control with use of a genetic algorithm.
Mechanical simulation of simple and double non-inertial pendula
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