DynaPlex is a software library for solving Markov Decision Problems and similar models (POMDP, HMM) written primarily in C++20 with bindings for python. It supports deep reinforcement learning, approximate dynamic programming, classical parameterized policies, and exact methods based on policy and value iteration. Models in DynaPlex are written in C++, and exposed via a generic and vectorized interface.
DynaPlex focuses on solving problems arising in Operations Management: Supply Chain, Transportation and Logistics, Manufacturing, etc.
Cloning the Repository with Dependencies¶
When cloning the repository, it’s essential to also download the required submodules:
`bash
git clone --recurse-submodules https://github.com/DynaPlex/DynaPlex.git
`
if you did not recurse submodules, or if you use other tools for cloning repos, please somehow ensure that submodules (especially googletest) are available.
Note
If you are new to MDPs, you might benefit from first reading the introduction to MDPs and going thorugh the step-by-step tutorial, starting with the MDP formulation pages. If you just want to know how to install, setup, and add a model, see the docs under “Getting started”
Contents¶
Getting started
Tutorial
Reference
- Modelling reference
- Custom policy reference
- Exact policy reference
- Event class reference
- MDP class reference
- State class reference
- Tester class reference
Algorithms
Getting help and Contributing
Troubleshooting
Legacy