TY - GEN
T1 - Cascaded generic XCS to learn about reminding preferences
AU - Richard, Nadine
AU - Tardieu, Samuel
AU - Yamada, Seiji
PY - 2007/8/27
Y1 - 2007/8/27
N2 - We are developing an adaptive reminding system, which learns when and how to present notifications. In this paper, we focus on our XCS-based model, composed of two cascaded sets of classifiers: the first one learns a categorization of calendar data, while the second selects the appropriate forms of combinable reminders depending on the user and device contexts. After describing the characteristics of the input data, we present the extensions we propose to provide a generic XCS architecture, which seems suitable for processing those specific inputs. Finally, we describe our user feedback mechanism, and the according reward system.
AB - We are developing an adaptive reminding system, which learns when and how to present notifications. In this paper, we focus on our XCS-based model, composed of two cascaded sets of classifiers: the first one learns a categorization of calendar data, while the second selects the appropriate forms of combinable reminders depending on the user and device contexts. After describing the characteristics of the input data, we present the extensions we propose to provide a generic XCS architecture, which seems suitable for processing those specific inputs. Finally, we describe our user feedback mechanism, and the according reward system.
KW - Adaptive reminders
KW - Learning classifier systems
KW - Personal time management
UR - https://www.scopus.com/pages/publications/34548096131
U2 - 10.1145/1274000.1274062
DO - 10.1145/1274000.1274062
M3 - Conference contribution
AN - SCOPUS:34548096131
SN - 159593698X
SN - 9781595936981
T3 - Proceedings of GECCO 2007: Genetic and Evolutionary Computation Conference, Companion Material
SP - 2923
EP - 2926
BT - Proceedings of GECCO 2007
T2 - 9th Annual Genetic and Evolutionary Computation Conference, GECCO 2007
Y2 - 7 July 2007 through 11 July 2007
ER -