Java and Python wrapper for a use case of the PDDL library of the Julia language (PDDL.jl)
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The general behavior of the program is defined inside the Planner.jl file.
The Julia file contains the kernel of the project where you can choose which file you need to solve by changing the domain and problem files.
The Planner.py file is a simple wrapper to the Planner.jl file, it replicates the behaviour of the original planner and prints the results to the standard output.
The Planner.java file runs the python wrapper and measures the time of execution.
This project has been tested on a Debian 11 distro.
- Julia
- Python 3
- JDK
- python-jl
- Clone the repo
git clone https://github.com/hurxan/JuPyJava_Planner.git
The examples folder contains some domains and problems taken from PlanningDomains.jl.
Inside the Planner.jl file you can choose which domain and problem file to use and which algorithm and heuristic suits better for your usage.
As a result, at the end of the execution a txt file (ie. blocksworld_problem-9_greedyplanner_hmax.txt) for each solution will be placed inside the output folder.
The generated file contains the solution of the planning based on the algorithm and heuristics chosen.
Contributions are highly appreciated.
If you have a suggestion that would make this better, please fork the repo and create a pull request.
- Fork the Project
- Create your Feature Branch (
git checkout -b feature/AmazingFeature) - Commit your Changes (
git commit -m 'Add some AmazingFeature') - Push to the Branch (
git push origin feature/AmazingFeature) - Open a Pull Request