Παρακαλώ χρησιμοποιήστε αυτό το αναγνωριστικό για να παραπέμψετε ή να δημιουργήσετε σύνδεσμο προς αυτό το τεκμήριο: https://ruomo.lib.uom.gr/handle/7000/497
Τίτλος: Alternative Plan Generation and Online Preference Learning in Scheduling Individual Activities
Συγγραφείς: Alexiadis, Anastasios
Refanidis, Ioannis
Τύπος: Article
Θέματα: FRASCATI::Natural sciences::Computer and information sciences
Λέξεις-Κλειδιά: intelligent calendar applications
scheduling
learning
Ημερομηνία Έκδοσης: 2016
Εκδότης: World Scientific
Πηγή: International Journal on Artificial Intelligence Tools
Τόμος: 25
Τεύχος: 03
Πρώτη Σελίδα: 1650014
Επιτομή: This article tackles a significant aspect of the problem of scheduling personal individual activities, that is, the generation of qualitative, significantly different alternative plans. Solving this problem is important for intelligent calendar applications, since average users cannot adequately express their preferences over the way their activities should be scheduled in time, thus it is common that they are not satisfied by the plans generated for them by a scheduler, although they are near-optimal according to their stated preferences. Hence generating alternative plans and asking the user to select one among them is a sensible approach, provided that the alternative plans are both near-optimal, according to the user-defined preferences, as well as significantly different to each other, in order to increase the chances that at least one of them satisfies the user. Furthermore, based on the assumption that a user might systematically misweight his preferences over the various aspects of a plan, an online non-intrusive method to learn his actual preferences is presented, based on monitoring his selections over the alternative plans. The proposed methods have been evaluated successfully on a variety of problems. Furthermore, they have been implemented in two deployed systems.
URI: https://doi.org/10.1142/S0218213016500147
https://ruomo.lib.uom.gr/handle/7000/497
ISSN: 0218-2130
Ηλεκτρονικό ISSN: 1793-6349
Αλλοι Προσδιοριστές: 10.1142/S0218213016500147
Εμφανίζεται στις Συλλογές: Τμήμα Εφαρμοσμένης Πληροφορικής

Αρχεία σε αυτό το Τεκμήριο:
Αρχείο Περιγραφή ΜέγεθοςΜορφότυπος 
IJAIT-D-15-00003_R2 - Copy.pdfsecond revision8,32 MBAdobe PDFΠροβολή/Ανοιγμα


Τα τεκμήρια στο Αποθετήριο προστατεύονται από πνευματικά δικαιώματα, εκτός αν αναφέρεται κάτι διαφορετικό.