Temporal Fast Downward

This is a slightly modified version of TFD v0.4 (from IPC 2014).

What is TFD? TFD is a temporal planning system that successfully participated in the temporal satisficing track of the 6th International Planning Competition 2008. It is released under the terms of the GPL. A snapshot of the source code is available in the download section.

The algorithms used in TFD are described in the ICAPS 2009 paper [1]. TFD is based on the Fast Downward planning system and uses an adaptation of the context-enhanced additive heuristic [2] to guide the search in the temporal state space induced by the given planning problem.

TFD is mainly developed by Gabriele Röger, Patrick Eyerich, Christian Dornhege, and Robert Mattmüller.

Original Links

• Homepage
• Downloads
• Contact

Installation

git clone https://github.com/neighthan/tfd
cd tfd
./build

Usage

downward/tfd domain_path problem_path solution_path [planner_config]

You can find a several benchmark domain and problem files in the benchmarks directory. To test your installation, try running

woodworking-numeric takes 0.01 seconds, plan takes 50 seconds

downward/tfd benchmarks/openstacks-numericadl/domain.pddl benchmarks/openstacks-numericadl/p01.pddl plan.txt

• This should take around 5 minutes to generate an optimal plan. The duration of the optimal plan should be about 82 seconds.
• The planner will periodically output improved plans, numbered sequentially as plan.txt.1, plan.txt.2, etc. until it times out or finds the optimal plan.

You can add a symlink to tfd/downward/tfd from somewhere on your path (e.g. ~/bin) to run this command from anywhere.

Modifications

• convert from python 2 to 3 + python formatting changes
• rename plan.py to tfd, make it robust to running from different directories, delete the intermediate files by default
• don't treat errors as warnings during compilation

Citation

If you use TFD in your research, please cite

@inproceedings{Eyerich2009UsingTC,
  title={Using the Context-enhanced Additive Heuristic for Temporal and Numeric Planning},
  author={Patrick Eyerich and Robert Mattm{\"u}ller and Gabriele R{\"o}ger},
  booktitle={ICAPS},
  year={2009}
}