clingexplaid 1.1.0

Tools to aid the development of explanation systems using clingo

clingexplaid

API to aid the development of explanation systems using clingo

Installation

Clingo-Explaid easily be installed with pip:

pip install clingexplaid

Requirements

• python >= 3.9
• clingo >= 5.7.1

Building from Source

Please refer to DEVELOPEMENT

API

Here are two example for using clingexplaid's API.

Minimal Unsatisfiable Subsets (MUS)

import clingo
from clingexplaid.transformers import AssumptionTransformer
from clingexplaid.mus import CoreComputer

PROGRAM = """
a(1..3).
{b(4..6)}.

a(X) :- b(X).

:- a(X), X>=3.
"""

control = clingo.Control()
at = AssumptionTransformer(signatures={("a", 1)})

transformed_program = at.parse_string(PROGRAM)

control.add("base", [], transformed_program)
control.ground([("base", [])])

assumptions = at.get_assumption_literals(control)

cc = CoreComputer(control, assumptions)


def shrink_on_core(core) -> None:
    mus_literals = cc.shrink(core)
    print("MUS:", cc.mus_to_string(mus_literals))


control.solve(assumptions=list(assumptions), on_core=shrink_on_core)

Unsatisfiable Constraints

from clingexplaid.unsat_constraints import UnsatConstraintComputer

PROGRAM = """
a(1..3).
{b(4..6)}.

a(X) :- b(X).

:- a(X), X>=3.
"""

ucc = UnsatConstraintComputer()
ucc.parse_string(PROGRAM)
unsat_constraints = ucc.get_unsat_constraints()

for uc_id, unsat_constraint in unsat_constraints.items():
    print(f"Unsat Constraint {uc_id}:", unsat_constraint)