OMTPlan provides a Python framework for cost-optimal planning in numeric domains.

Obtaining OMTPlan

Clone the OMTPlan repository in your favourite folder.

git clone https://github.com/fraleo/OMTPlan.git

Dependencies

To run OMTPlan, make sure you have the following on your machine

Python 2.7
Z3 (4.8.6) and its Python API. Make sure you add z3 Python bindings to your Python search path.
NetworkX (as simple as pip install networkx)
the VAL plan validation software. Here you can find some instructions to help you set it up. Once built, add the validate binary to the /bin folder.

Already provided within this repo are the following external modules

A modified version of the Temporal Fast Downward Python parser.

Using OMTPlan

Getting help

To see the list of input arguments, type

./omtplan -h

Running OMTPlan

To run OMTPlan on a problem, type, e.g.,

./omtplan -omt -parallel -domain domain.pddl problem.pddl

or

./omtplan -omt -parallel problem.pddl

if PDDL files describing domain and problem are in the same folder.

Translating to SMT-LIB

To produce an SMT-LIB encoding of the bounded planning problem, type, e.g.,

./omtplan.py -smt -parallel -translate bound problem.pddl

Some PDDL examples

You can find some planning problems written in PDDL in pddl_examples.

Documentation

Further documentation is available here.

Author

Francesco Leofante

Do not hesitate to contact me if you have problems using OMTPlan, or if you find bugs :)

Citing OMTPlan

If you decide to use OMTPlan for your experiments, please cite

@inproceedings{LeofanteGAT20,
  author    = {Francesco Leofante and
           Enrico Giunchiglia and
           Erika {\'{A}}brah{\'{a}}m and
           Armando Tacchella},
  editor    = {Christian Bessiere},
  title     = {Optimal Planning Modulo Theories},
  booktitle = {Proceedings of the Twenty-Ninth International Joint Conference on
           Artificial Intelligence, {IJCAI} 2020 },
  pages     = {4128--4134},
  publisher = {ijcai.org},
  year      = {2020},
  url       = {https://doi.org/10.24963/ijcai.2020/571}
}