Metadata-Version: 2.1
Name: pyperplan
Version: 1.0
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: This is **Pyperplan**, 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-get install python3
        
        will install Python 3 on an Ubuntu system.
        
        Versions of Python before Python 3.2 lack the argparse package, which Pyperplan
        uses for command line argument parsing. A copy of the argparse package is
        included with the planner and will be used automatically if no preinstalled
        version can be found.
        
        
        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.txt.
        
        
        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.
        
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/x-rst
