Metadata-Version: 2.1
Name: pyperplan
Version: 1.3
Summary: A lightweight STRIPS planner written in Python.
Home-page: https://github.com/aibasel/pyperplan
Author: Jendrik Seipp
Author-email: jendrik.seipp@unibas.ch
License: GPL3+
Description: **Pyperplan** is a lightweight STRIPS planner written in Python.
        
        Please note that Pyperplan deliberately prefers clean code over fast
        code. It is designed to be used as a teaching or prototyping tool. If
        you use it for paper experiments, please state clearly that Pyperplan
        does not offer state-of-the-art performance.
        
        It was developed during the planning practical course at
        Albert-Ludwigs-Universität Freiburg during the winter term 2010/2011 and
        is published under the terms of the GNU General Public License 3
        (GPLv3).
        
        Pyperplan supports the following PDDL fragment: STRIPS without action
        costs. This file only gives the basic information to get you up and
        running. The full documentation can be found in the doc directory. You
        can either read the text file documentation.txt directly or run "make"
        in the doc directory to convert it to a PDF document.
        
        # Requirements
        
        Pyperplan is written in Python 3, so you need a recent version of Python
        3 installed to run it. If Python 3 is not installed on your system, you
        can download it from <http://python.org>. Alternatively, most current
        Linux distributions include Python 3. For example,
        
        > sudo apt install python3
        
        will install Python 3 on an Ubuntu system.
        
        # Usage
        
        The planner is invoked through the file src/pyperplan.py and accepts two
        arguments: a PDDL domain file and a PDDL problem file. Example:
        
        > ./src/pyperplan.py benchmarks/tpp/domain.pddl
        > benchmarks/tpp/task01.pddl
        
        The domain file can be omitted, in which case the planner will attempt
        to guess its name based on the problem file. If a plan is found, it is
        stored alongside the problem file with a .soln extension.
        
        By default, the planner performs a blind breadth-first search, which
        does not scale very well. Heuristic search algorithms are available. For
        example, to use greedy-best-first search with the FF heuristic, run
        
        > ./src/pyperplan.py -H hff -s gbf DOMAIN PROBLEM
        
        For a list of available search algorithms and heuristics, run
        
        > ./src/pyperplan.py --help
        
        For more information on using the planner and how to extend it to do
        more fancy stuff, see doc/documentation.md.
        
        # Contact
        
        Pyperplan is hosted on GitHub: <https://github.com/aibasel/pyperplan>
        
        The original authors of Pyperplan are, in alphabetical order:
        
          - Yusra Alkhazraji
          - Matthias Frorath
          - Markus Grützner
          - Thomas Liebetraut
          - Manuela Ortlieb
          - Jendrik Seipp
          - Tobias Springenberg
          - Philip Stahl
          - Jan Wülfing
        
        The instructors of the course in which Pyperplan was created were Malte
        Helmert and Robert Mattmüller.
        
        If you want to get in touch with us, please contact Robert Mattmüller or
        Jendrik Seipp. Their email addresses can easily be found on the web.
        
        # Citing Pyperplan
        
        Please cite Pyperplan using
        
            @Misc{alkhazraji-et-al-zenodo2020,
              author =       "Yusra Alkhazraji and Matthias Frorath and Markus Gr{\"u}tzner
                              and Malte Helmert and Thomas Liebetraut and Robert Mattm{\"u}ller
                              and Manuela Ortlieb and Jendrik Seipp and Tobias Springenberg and
                              Philip Stahl and Jan W{\"u}lfing",
              title =        "Pyperplan",
              publisher =    "Zenodo",
              year =         "2020",
              doi =          "10.5281/zenodo.3700819",
              url =          "https://doi.org/10.5281/zenodo.3700819",
              howpublished = "\url{https://doi.org/10.5281/zenodo.3700819}"
            }
        
Keywords: classical planning STRIPS
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Environment :: Console
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: GNU General Public License v3 or later (GPLv3+)
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Topic :: Scientific/Engineering
Requires-Python: >=3.5
Description-Content-Type: text/markdown
