Logical Conditional Preference Theories
Abstract
CP-nets represent the dominant existing framework for expressing qualitative conditional preferences between alternatives, and are used in a variety of areas including constraint solving. Over the last fifteen years, a significant literature has developed exploring semantics, algorithms, implementation and use of CP-nets. This paper introduces a comprehensive new framework for conditional preferences: logical conditional preference theories (LCP theories). To express preferences, the user specifies arbitrary (constraint) Datalog programs over a binary ordering relation on outcomes. We show how LCP theories unify and generalize existing conditional preference proposals, and leverage the rich semantic, algorithmic and implementation frameworks of Datalog.
Cite
@article{arxiv.1504.06374,
title = {Logical Conditional Preference Theories},
author = {Cristina Cornelio and Andrea Loreggia and Vijay Saraswat},
journal= {arXiv preprint arXiv:1504.06374},
year = {2015}
}
Comments
15 pages, 1 figure, submitted to CP 2015