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FastDownward

A slightly modified version of Fast Downward.

Information

Fast Downward is a domain-independent planning system.

For documentation and contact information see http://www.fast-downward.org/.

The following directories are not part of Fast Downward as covered by this license:

  • ./src/search/ext

For the rest, the following license applies:

Fast Downward is free software: you can redistribute it and/or modify it under
the terms of the GNU General Public License as published by the Free Software
Foundation, either version 3 of the License, or (at your option) any later
version.

Fast Downward is distributed in the hope that it will be useful, but WITHOUT ANY
WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A
PARTICULAR PURPOSE. See the GNU General Public License for more details.

You should have received a copy of the GNU General Public License along with
this program. If not, see <http://www.gnu.org/licenses/>.

Installation

Run the following commands:

$ git clone https://github.com/caelan/FastDownward.git
$ cd FastDownward
$ python ./build.py

Many development systems already satisfy FastDownward's dependencies. If ./build.py fails, install FastDownward's dependencies using your package manager:

  • APT (Linux): $ sudo apt-get install cmake g++ g++-multilib make python
  • Homebrew (OS X): TBD
  • MacPorts (OS X): TBD
  • Windows:
    1. Install VS Studio Build Tools by downloading and running the executable from here. Select the C++ Build Tools option in the installer.
    2. Install CMake in your python environment by pip install cmake.
    3. Search for Developer Command Prompt for VS 2017 in your search bar and run it.
    4. In the Developer Command Prompt for VS 2017, issue: 
      cd /d "<path to FastDownward>"
python ./build.py

If necessary, see FastDownward's documentation for more detailed installation instructions:

http://www.fast-downward.org/ObtainingAndRunningFastDownward

Citation

Malte Helmert. The Fast Downward Planning System. Journal of Artificial Intelligence Research 26, pp. 191-246. 2006.