TY  - GEN
A1  - Alviano, Mario
A1  - Romero Davila, Javier
A1  - Schaub, Torsten H.
T1  - Preference Relations by Approximation
T2  - Sixteenth International Conference on Principles of Knowledge Representation and Reasoning
N2  - Declarative languages for knowledge representation and reasoning provide constructs to define preference relations over the set of possible interpretations, so that preferred models represent optimal solutions of the encoded problem. We introduce the notion of approximation for replacing preference relations with stronger preference relations, that is, relations comparing more pairs of interpretations. Our aim is to accelerate the computation of a non-empty subset of the optimal solutions by means of highly specialized algorithms. We implement our approach in Answer Set Programming (ASP), where problems involving quantitative and qualitative preference relations can be addressed by ASPRIN, implementing a generic optimization algorithm. Unlike this, chains of approximations allow us to reduce several preference relations to the preference relations associated with ASP’s native weak constraints and heuristic directives. In this way, ASPRIN can now take advantage of several highly optimized algorithms implemented by ASP solvers for computing optimal solutions
Y1  - 2018
UR  - https://publishup.uni-potsdam.de/frontdoor/index/index/docId/53929
SP  - 2
EP  - 11
PB  - AAAI Conference on Artificial Intelligence
CY  - Palo Alto
ER  -