Metadata-Version: 2.1
Name: plan4past
Version: 0.1.0
Summary: Classical and FOND Planning for Pure-Past Linear Temporal Logic Goals
Home-page: https://whitemech.github.io/plan4past
License: LGPLv3+ license
Keywords: automated planning,temporally extended goals,pure-past linear temporal logic
Author: Luigi Bonassi
Author-email: luigi.bonassi@unibs.it
Requires-Python: >=3.8.1,<4.0
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: GNU Lesser General Public License v3 or later (LGPLv3+)
Classifier: License :: Other/Proprietary License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.8
Requires-Dist: click (>=8.1.3,<9.0.0)
Requires-Dist: pddl (>=0.3.1,<0.4.0)
Requires-Dist: pylogics (>=0.2.1,<0.3.0)
Project-URL: Bug Tracker, https://github.com/whitemech/plan4past/issues
Project-URL: Documentation, https://whitemech.github.io/plan4past
Project-URL: Pull Requests, https://github.com/whitemech/plan4past/pulls
Project-URL: Repository, https://github.com/whitemech/plan4past.git
Description-Content-Type: text/markdown

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</h1>

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---

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.

```python
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](https://python-poetry.org)
- 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](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).

