Planning Engines Examples

We present here a list of notebooks, divided by planning approaches.

Classical Planning

  • In this notebook we show how to model and solve classical problems:

    Open In GitHub Open In Colab

  • In this notebook we show how to add optimization metrics and solve the problem optimally:

    Open In GitHub Open In Colab

  • In this (external) notebook we demonstrate the capabilities of the Fast Downward engines (including anytime operation mode, grounding and advanced topics such as using alternative configurations and troubleshooting):

    Open In GitHub Open In Colab

Numeric Planning

Temporal Planning

  • In this notebook we show how to use the unified planning library to model temporal problems.

    Open In GitHub Open In Colab

Multi-agent Planning

  • In this notebook shows how to use the unified planning library to model simple multi-agent problems and what heuristics the planner supports.

    Open In GitHub Open In Colab

  • In this notebook we show how to use the unified planning library to model multi-agent problems. In particular we model the well-known Depot problem and we call a planner to solve it.

    Open In GitHub Open In Colab

Refinement Planning

  • In this notebook, we show how to use unified planning library to define hierrachical planning problem.

    Open In GitHub Open In Colab

Combined Task and Motion Planning

  • In this notebook, we show how to use unified planning library to combined task and motion planning problem.

    Open In GitHub Open In Colab