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Quick start

Starting with Fast Downward 19.06, we provide Docker and Singularity images as well as a recommended Vagrant configuration file in order to make the use of the planner as easy as possible. Of course, you can still build Fast Downward from the source code. We provide below a few instructions to get you started as quickly as possible, but you can find a more detailed description on PlannerUsage and ObtainingAndRunningFastDownward.

Recommended use cases. If you want to run experiments, we recommend using the Docker or Singularity images. Both should have a small performance overhead, so you should pick the one supported by your cluster. The Vagrantfile includes all Fast Downward's source code and is mainly intended for teaching and demonstration purposes. It should not be used to run experiments. If you want to develop on top of Fast Downward, we recommend starting either from a fork of the repository or the tarball.

Running the Docker image

Let us assume that you have Docker installed on your machine and want to solve a planning problem located on the $BENCHMARKS directory. You can run the satisficing LAMA configuration of the planner:

   1 docker run --rm -v $BENCHMARKS:/benchmarks aibasel/downward --alias lama-first /benchmarks/gripper/prob01.pddl

Note that this mounts the local directory $BENCHMARKS of your host machine under the container directory /benchmarks, which is the place where the containerized planner reads the problems from. The path stored in the $BENCHMARKS variable needs to be absolute.

Running the Singularity image

Let us assume that you have Singularity installed on your machine (we have tested this with Singularity 2.6 and 3.2), and want to solve a planning problem located on the $BENCHMARKS directory. You can run the same LAMA configuration as before:

   1 singularity pull --name downward.simg shub://aibasel/downward
   2 singularity run downward.simg --alias lama-first $BENCHMARKS/gripper/prob01.pddl

The first command downloads the Singularity image into the local file downward.simg, while the second command is the one running Fast Downward from this image. Unlike Docker, $BENCHMARKS does not have to be an absolute path.

Using a Vagrant machine

Assuming that you have Vagrant installed on your machine, you can use the Fast Downward Vagrantfile as follows:

Place the Vagrantfile for the desired release into some empty directory.
Put your PDDL files into the same directory as the Vagrantfile, say, under names domain.pddl and problem.pddl.
Navigate to this directory and type vagrant up.
Log into the Vagrant virtual machine by typing vagrant ssh.
Run downward/fast-downward.py --alias lama-first /vagrant/domain.pddl /vagrant/problem.pddl.
Type exit to leave the virtual machine, then vagrant halt to stop it.

Source code

See ObtainingAndRunningFastDownward for a complete description on how to build the planner from source.

Next steps

See other ways of invoking the planner on PlannerUsage.
Read about recommended experiment setups.
Go through the full Documentation.

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