A Constraint Logic Programming Approach for Computing Ordinal Conditional Functions
Abstract
In order to give appropriate semantics to qualitative conditionals of the form "if A then normally B", ordinal conditional functions (OCFs) ranking the possible worlds according to their degree of plausibility can be used. An OCF accepting all conditionals of a knowledge base R can be characterized as the solution of a constraint satisfaction problem. We present a high-level, declarative approach using constraint logic programming techniques for solving this constraint satisfaction problem. In particular, the approach developed here supports the generation of all minimal solutions; these minimal solutions are of special interest as they provide a basis for model-based inference from R.
Cite
@article{arxiv.1108.5794,
title = {A Constraint Logic Programming Approach for Computing Ordinal Conditional Functions},
author = {Christoph Beierle and Gabriele Kern-Isberner and Karl Södler},
journal= {arXiv preprint arXiv:1108.5794},
year = {2011}
}
Comments
To appear in the Proceedings of the 25th Workshop on Logic Programming (WLP 2011)