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Tools to aid the development of explanation systems using clingo

Project description

clingexplaid

Tools 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

Usage

Run the following for basic usage information:

clingexplaid -h

The clingexplaid CLI (based on the clingo.Application class) can be called using this generic command.

clingexplaid <filenames> <n> <method> <options>
  • <filenames>: has to be replaced by a list of all files or a single filename
  • <n>: defines how many models are computed (Default=1, All=0)
  • <method>: specifies which Clingexplaid method is used (Required)
    • Options:
      • --muc:
        • Computes the Minimal Unsatisfiable Cores (MUCs) of the provided unsatisfiable program
      • --unsat-constraints:
        • Computes the Unsatisfiable Constraints of the unsatisfiable program provided.
      • --show-decisions:
        • Visualizes the decision process of clasp
  • <options>: Additional options for the different methods
    • For --muc:
      • -a, --assumption-signature: limits which facts of the current program are converted to choices/assumptions for finding the MUCs (Default: all facts are converted)
    • For --show-decisions:
      • --decision-signature: limits which decisions are shown in the visualization (Default: all atom's decisions are shown)

Examples

Given the simple program below simple.lp we want to find the contained MUC (Minimal Unsatisfiable Core).

a(1..5).
b(5..10).

:- a(X), b(X).

For this we can call clingexplaid the following way:

clingexplaid examples/misc/simple.lp --muc 0

This converts all facts of the program to choices and assumptions and returns the contained MUC from that.

MUC  1
b(5) a(5)

A selection of more examples can be found here

Project details


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