Skip to main content

Python Version PyPI build codecov GitHub


Classical and FOND Planning for Pure-Past Linear Temporal Logic Goals.

Installation

  • from PyPI:
pip install plan4past
  • from source (main branch):
pip install git+https://github.com/whitemech/Plan4Past.git

or, clone the repository and install:

git clone https://github.com/whitemech/Plan4Past.git
cd Plan4Past
pip install .

Quickstart

You can use the plan4past package in two ways: as a library, and as a CLI tool.

As a library

This is an example of how you can encode a PPLTL goal formula into a PDDL domain and problem programmatically.

from pathlib import Path
from pddl.formatter import domain_to_string, problem_to_string
from pddl.parser.domain import DomainParser
from pddl.parser.problem import ProblemParser
from pylogics.parsers import parse_pltl
from plan4past.compiler import Compiler

formula = "on_b_a & O(ontable_c)"
domain_parser = DomainParser()
problem_parser = ProblemParser()

domain = domain_parser(Path("examples/pddl/domain.pddl").read_text(encoding="utf-8"))
problem = problem_parser(Path("examples/pddl/p-0.pddl").read_text(encoding="utf-8"))
goal = parse_pltl(formula)

compiler = Compiler(domain, problem, goal)
compiler.compile()
compiled_domain, compiled_problem = compiler.result

try:
    with open("./new-domain.pddl", "w+", encoding="utf-8") as d:
        d.write(domain_to_string(compiled_domain))
    with open("./new-problem.pddl", "w+", encoding="utf-8") as p:
        p.write(problem_to_string(compiled_problem))
except Exception as e:
    raise IOError(
        "[ERROR]: Something wrong occurred while writing the compiled domain and problem."
    ) from e

By executing the code above, you will obtain a new-domain.pddl as well as a new-problem.pddl in output.

As a CLI tool

The package can also be used as a CLI tool. The supported command is:

plan4past -d DOMAIN_FILE -p PROBLEM_FILE -g "PPLTL_FORMULA" [-m MAPPING] 

where DOMAIN_FILE and PROBLEM_FILE are the PDDL domain and problem files, respectively, and PPLTL_FORMULA is the goal formula expressed in Pure-Past Linear Temporal Logic. The optional MAPPING file is a mapping between the PDDL objects and the PPLTL formula's atomic propositions.

For instance:

plan4past -d examples/pddl/domain.pddl -p examples/pddl/p-0.pddl -g "ontable_c & O(on_b_a)"

Docker & Apptainer images

A Docker image as well as an Apptainer image are available for Plan4Past.

  • To use Docker: docker build -t plan4past . and docker run --rm -it plan4past

  • To use Apptainer:

apptainer build plan4past.sif plan4past.def

# to launch the tool:
./plan4past.sif -d examples/pddl/domain.pddl -p examples/pddl/p-0.pddl -g "ontable_c & O(on_b_a)"

Development

If you want to contribute, set up your development environment as follows:

  • Intall Poetry
  • Clone the repository: git clone https://github.com/whitemech/Plan4Past.git && cd Plan4Past
  • Install the dependencies: poetry shell && poetry install

Docs

To build the docs: mkdocs build

To view documentation in a browser: mkdocs serve and then go to http://localhost:8000

License

Plan4Past is released under the GNU Lesser General Public License v3.0 or later (LGPLv3+).

Copyright 2021 -- 2023 WhiteMech

Citing

If you use Plan4Past in your research, please consider citing the following paper:

@inproceedings{icaps2023bdffgs,
  author       = {Luigi Bonassi and 
                  Giuseppe {De Giacomo} and 
                  Marco Favorito and 
                  Francesco Fuggitti and 
                  {Alfonso Emilio} Gerevini and 
                  Enrico Scala},
  title        = {Planning for Temporally Extended Goals in Pure-Past Linear Temporal Logic},
  booktitle    = {{ICAPS}},
  volume       = {33},
  url          = {https://ojs.aaai.org/index.php/ICAPS/article/view/27179},
  doi          = {10.1609/icaps.v33i1.27179},
  number       = {1},
  month        = {Jul.},
  pages        = {61-69},
  year         = {2023},
}

Acknowledgements

Plan4Past has been partially supported by the EU H2020 project AIPlan4EU (No. 101016442), the ERC-ADG WhiteMech (No. 834228), the EU ICT-48 2020 project TAILOR (No. 952215), the PRIN project RIPER (No. 20203FFYLK), and the PNRR MUR project FAIR (No. PE0000013).

Metadata

Release files for plan4past 0.1.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for plan4past 0.1.0
File Size Uploaded Provenance
plan4past-0.1.0.tar.gz 15.9 kB Without provenance Details

Built distribution (wheel)

Table of built distributions (wheels) for plan4past 0.1.0
File Interpreter ABI Platform
plan4past-0.1.0-py3-none-any.whl Python 3 none any Details

Total release size: 39.0 kB

Release files / plan4past-0.1.0.tar.gz

Download URL plan4past-0.1.0.tar.gz
Size 15.9 kB
Tags Source
SHA-256 checksum
How to use checksums
9456a7705b8f4c3df62e34f59f9a551c45f887d145c5a7a40704f74a2769c310
BLAKE2b-256 checksum
How to use checksums
e0da28b9d30aa731a8593f23a9297cd24f60537d149ca96dcdd7a48c21a51a69
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.2 CPython/3.10.11

Release files / plan4past-0.1.0-py3-none-any.whl

Download URL plan4past-0.1.0-py3-none-any.whl
Size 23.1 kB
Tags Python 3
SHA-256 checksum
How to use checksums
8641a9f738e11d8c83f890b6e418b27f8ff5c192a81a01b87fc8658ab01d52c8
BLAKE2b-256 checksum
How to use checksums
c03c3e8655982a72af55cec34bba9a0cde220d940ca2dcb5d461250bb8c2a76b
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.2 CPython/3.10.11

Security for plan4past 0.1.0

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

No provenance found

None of the files in this release were uploaded with provenance metadata.

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

To learn more about protecting yourself from malicious actors, visit our package security documentation.

Release history Release notifications | RSS feed

This release

0.1.0 This release

2 release files No provenance

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page