Répertoire de publications
de recherche en accès libre
de recherche en accès libre
Brooks, Martin; Yan, Yuhong et Lemire, Daniel (2005). Scale-Based Monotonicity Analysis in Qualitative Modelling with Flat Segments. Dans Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence. Edinburgh, UK : IJICAI.
Fichier(s) associé(s) à ce document :| PDF - ijcai05_web.pdf |
|
| Catégorie de document : | Communications dans des actes de congrès/colloques |
|---|---|
| Évaluation par un comité de lecture : | Oui |
| Étape de publication : | Publié |
| Résumé : | Qualitative models are often more suitable than classical quantitative models in tasks such as Model-based Diagnosis (MBD), explaining system behavior, and designing novel devices from first principles. Monotonicity is an important feature to leverage when constructing qualitative models. Detecting monotonic pieces robustly and efficiently from sensor or simulation data remains an open problem. This paper presents scale-based monotonicity: the notion that monotonicity can be defined relative to a scale. Real-valued functions defined on a finite set of reals e.g. sensor data or simulation results, can be partitioned into quasi-monotonic segments, i.e. segments monotonic with respect to a scale, in linear time. A novel segmentation algorithm is introduced along with a scale-based definition of "flatness". |
| Adresse de la version officielle : | http://www.ijcai.org/papers/0890.pdf |
| Déposant: | Lemire, Daniel |
| Responsable : | Daniel Lemire |
| Dépôt : | 05 juin 2007 |
| Dernière modification : | 16 juill. 2015 00:47 |
|
RÉVISER |
