Tarski - An AI Planning Modeling Framework

What is Tarski

Tarski is a framework for the specification, modeling and manipulation of AI planning problems. Tarski is written in Python and includes parsers for major modeling languages (e.g., PDDL, FSTRIPS, RDDL), along with modules to perform common tasks such as reachability analysis and grounding of first-order representations.

Installation

You can install the latest Tarski release with

pip install tarski

If instead you want to use the latest code available on the Github repository, use

pip install -U git+https://github.com/aig-upf/tarski.git

Development

If developing Tarski, we recommend cloning from the Github repository and doing a dev installation (the-e flag for pip) on a virtual environment:

git clone https://github.com/aig-upf/tarski
cd tarski
pip install -e .

This will install the project in "editable mode", meaning that any modification to the files is immediately reflected in the installed library.

Testing

All of Tarski's tests live under the tests directory (shocking!). To run them, you just need to run pytest (pip install pytest) on the root directory. You can also run tox (pip install tox) to have some additional checks (e.g., style checks) run.

Software Requirements

Tarski requires Python >= 3.5. The above installation instructions will install transparently for you a number of additional dependencies, among which numpy, scipy and pyrddl.

Known Limitations

At the moment, Tarski is able to parse problems specified in PDDL, Functional STRIPS and RDDL, but (1) parsing of derived predicates is not supported yet, and (2) the PDDL either keyword for defining compound types is not supported, and it is unlikely it will ever be. Additionally, and for compatibility reasons with old standard benchmarks, the parser represents all predicate, function (including constants) and PDDL types (i.e. FOL sorts) in lowercase.