Treffer: Query-driven Qualitative Constraint Acquisition.

Title:
Query-driven Qualitative Constraint Acquisition.
Authors:
Belaid, Mohamed-Bachir1,2 BBEL@NILU.NO, Belmecheri, Nassim3 NASSIM@SIMULA.NO, Gotlieb, Arnaud3 ARNAUD@SIMULA.NO, Lazaar, Nadjib4 LAZAAR@LIRMM.FR, Spieker, Helge3 HELGE@SIMULA.NO
Source:
Journal of Artificial Intelligence Research. 2024, Vol. 79, p241-271. 31p.
Database:
Supplemental Index

Weitere Informationen

Many planning, scheduling or multi-dimensional packing problems involve the design of subtle logical combinations of temporal or spatial constraints. Recently, we introduced GEQCA-I, which stands for Generic Qualitative Constraint Acquisition, as a new active constraint acquisition method for learning qualitative constraints using qualitative queries. In this paper, we revise and extend GEQCA-I to GEQCA-II with a new type of query, universal query, for qualitative constraint acquisition, with a deeper query-driven acquisition algorithm. Our extended experimental evaluation shows the efficiency and usefulness of the concept of universal query in learning randomly-generated qualitative networks, including both temporal networks based on Allen's algebra and spatial networks based on region connection calculus. We also show the effectiveness of GEQCA-II in learning the qualitative part of real scheduling problems. [ABSTRACT FROM AUTHOR]