Gymnasium environments for saturation provers
Project description
gym-saturation
gym-saturation is a collection of Gymnasium environments for reinforcement learning (RL) agents striving to prove theorems. Currently, only theorems written in TPTP library formal language are supported.
There are two environments in gym-saturation following the same API: SaturationEnv: VampireEnv is a wrapper around a recent Vampire prover, and IProverEnv relies on an experimental version of iProver.
In contrast to monolithic architecture of a typical Automated Theorem Prover (ATP), gym-saturation gives different agents opportunities to select clauses themselves and train from their experience. Combined with a particular agent, gym-saturation can work as an ATP.
gym-saturation can be interesting for RL practitioners willing to apply their experience to theorem proving without coding all the logic-related stuff themselves. It also can be useful for automated deduction researchers who want to create an RL-empowered ATP.
How to Install
The best way to install this package is to use pip:
pip install gym-saturation
Another option is to use conda:
conda install -c conda-forge gym-saturation
One can also run it in a Docker container (pre-packed with vampire and iproveropt binaries):
docker build -t gym-saturation https://github.com/inpefess/gym-saturation.git
docker run -it --rm -p 8888:8888 gym-saturation jupyter-lab --ip=0.0.0.0 --port=8888
How to use
One can use gym-saturation environments as any other Gymnasium environment:
import gym_saturation
import gymnasium
env = gymnasium.make("Vampire-v0") # or "iProver-v0"
# skip this line to use the default problem
env.set_task("a-TPTP-problem-filename")
observation, info = env.reset()
terminated, truncated = False, False
while not (terminated or truncated):
# apply policy (a valid random action here)
action = env.action_space.sample(mask=observation["action_mask"])
observation, reward, terminated, truncated, info = env.step(action)
env.close()
Or have a look at the basic tutorial.
For a bit more comprehensive experiments, please navigate the documentation page.
How to Contribute
Pull requests are welcome. To start:
git clone https://github.com/inpefess/gym-saturation
cd gym-saturation
# activate python virtual environment with Python 3.8+
pip install -U pip
pip install -U setuptools wheel poetry
poetry install
# recommended but not necessary
pre-commit install
# install Vampire binary
wget https://github.com/vprover/vampire/releases/download/v4.7/vampire4.7.zip -O vampire.zip
unzip vampire.zip
# then use vampire_z3_rel_static_HEAD_6295 as an argument or add it to $PATH
# install iProver binary
wget https://gitlab.com/api/v4/projects/39846772/jobs/artifacts/2022.11.03/download?job=build-job -O iprover.zip
unzip iprover.zip
# then use iproveropt
All the tests in this package are doctests. One can run them with the following command:
pytest --doctest-modules gym-saturation
To check the code quality before creating a pull request, one might run the script local-build.sh. It locally does nearly the same as the CI pipeline after the PR is created.
Reporting issues or problems with the software
Questions and bug reports are welcome on the tracker.
More documentation
More documentation can be found here.
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