Expertini Research Research
Artificial Intelligence And Data Science PDF Available Non-peer-reviewed Preprint

Generalizing Modular Logic Programs

Joao Moura, Carlos Damasio  ·  Published 2014-04-29

Abstract

Even though modularity has been studied extensively in conventional logic programming, there are few approaches on how to incorporate modularity into Answer Set Programming, a prominent rule-based declarative programming paradigm. A major approach is Oikarinnen and Janhunen's Gaifman-Shapiro-style architecture of program modules, which provides the composition of program modules. Their module theorem properly strengthens Lifschitz and Turner's splitting set theorem for normal logic programs. However, this approach is limited by module conditions that are imposed in order to ensure the compatibility of their module system with the stable model semantics, namely forcing output signatures of composing modules to be disjoint and disallowing positive cyclic dependencies between different modules. These conditions turn out to be too restrictive in practice and in this paper we discuss alternative ways of lift both restrictions independently, effectively solving the first, widening the applicability of this framework and the scope of the module theorem.
📄 Full Paper Available as PDF
This paper is available as a downloadable PDF.
📄 Download PDF

✨ AI Plain-English Summary

Get a plain-English summary of this paper generated by AI (5 free per day).

Comments (0)

No comments yet. Be the first to comment.

Related Papers

Artificial Intelligence And Data Science PDF

Sparse matrix-variate Gaussian process blockmodels for network modeling

2012
Artificial Intelligence And Data Science PDF

Hierarchical Maximum Margin Learning for Multi-Class Classification

2012
Artificial Intelligence And Data Science PDF

Tightening MRF Relaxations with Planar Subproblems

2012
Artificial Intelligence And Data Science PDF

Rank/Norm Regularization with Closed-Form Solutions: Application to ...

2012