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DDPG algorithm on an inverted pendulum environment using Mujoco(C++) and pytorch C++ front end.

Home Page: https://github.com/i-m-iron-man/libtorch_mujoco_DDPG

License: MIT License

CMake 8.20% C++ 91.80%
pytorch-cpp ddpg inverted-pendulum cpp pytorch-implementation pytorch-cpp-frontend deep-reinforcement-learning mujoco

libtorch_mujoco_ddpg's Introduction

Inverted Pendulum task

The task is to balance the pendulum upright using continuous control when the maximum torque available is not enough to overcome gravity. In this implementation a DDPG algorithm is used to learn the task. Mujoco libarary(http://www.mujoco.org/) is used to model the environment and pytorch c++ frontend(https://pytorch.org/cppdocs/frontend.html) provides the support for reinforcement learning framework.

Platform

  • OS: windows10(64 bit)
  • CUDA: 10.1
  • cuDNN: 7.6.3
  • Compiler: MSVC 19.28.29336.0
  • C++17
  • Cmake: 3.19.2

Dependencies

Instructions

  • In CMakeLists.txt replace C:/Users/kings/Desktop/source/mujoco200_win64/mujoco200_win64 at line 13 with the path to your mujoco installation
  • In CMakeLists.txt replace C:/Users/kings/Desktop/source/libtorch-mujoco-git at line 14 with the path to where you download these source files
  • open a command-prompt and cd to the location of these files
  • mkdir build && cd build
  • In order to build use command cmake -DCMAKE_PREFIX_PATH=<absolute path to libtorch>\libtorch ..
  • In order to make use command cmake --build . --config Release
  • In order to run first cd Release then libtorch-mujoco-git.exe ..\..\model\simple_pendulum.xml

Inspiration

https://github.com/EmmiOcean/DDPG_LibTorch

libtorch_mujoco_ddpg's People

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