Optimization of Just-in-Time Adaptive Interventions Using Reinforcement Learning

Date

2018-01-01

Author

Gonul, Suat
Namli, Tuncay
Baskaya, Mert
Sinaci, Ali Anil
Coşar, Ahmet
Toroslu, İsmail Hakkı

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

127
views

0
downloads

Momentary context data is an important source for intelligent decision making towards personalization of mobile phone notifications. We propose a reinforcement learning based personalized notification delivery algorithm, reasoning over momentary context data. Beyond the state of the art, we propose new approaches for faster convergence of the algorithm and jump start of learning performance at the beginning of the learning process. We test our approach in both simulated and real settings trying to optimize the timing of the notifications. Our eventual, practical aim is to make office workers more physically active during the work time. We compare the results obtained for standard and improved algorithms in both testbeds where improved versions yield better results.

Subject Keywords

Sedentary

URI

https://hdl.handle.net/11511/56210

DOI

https://doi.org/10.1007/978-3-319-92058-0_32

Collections

Graduate School of Natural and Applied Sciences, Conference / Seminar

Suggestions

OpenMETU
Core

Optimal data compression for lifetime maximization in wireless sensor networks operating in stealth mode Incebacak, Davut; Zilan, Ruken; TAVLI, BÜLENT; Barcelo-Ordinas, Jose M.; Garcia-Vidal, Jorge (2015-01-01) Contextual privacy in Wireless Sensor Networks (WSNs) is concerned with protecting contextual information such as whether, when, and where the data is collected. In this context, hiding the existence of a WSN from adversaries is a desirable feature. One way to mitigate the sensor nodes' detectability is by limiting the transmission power of the nodes (Le., the network is operating in the stealth mode) so that adversaries cannot detect the existence of the WSN unless they are within the sensing range of the ...
Evaluation of a mobile phone based student immediate feedback system Çiçek, Filiz; İslim, Ömer Faruk; Çağıltay, Kürşat; Çapa Aydın, Yeşim (null; 2013-11-02) The purpose of this study is to explore a cell-phone Short Message Service (SMS) - based immediate feedback system and to reveal opinions of instructors. This study is designed as a qualitative one and data were collected via semi-structured interviews with 4 instructors who used the system in their classrooms. The significance of this study is to help to remove obstacles about the design of such cell-phone based immediate feedback systems and exploring pedagogical guidelines/principles.
Fusion of multimodal information for multimedia information retrieval Yılmaz, Turgay; Yazıcı, Adnan; Department of Computer Engineering (2014) An effective retrieval of multimedia data is based on its semantic content. In order to extract the semantic content, the nature of multimedia data should be analyzed carefully and the information contained should be used completely. Multimedia data usually has a complex structure containing multimodal information. Noise in the data, non-universality of any single modality, and performance upper bound of each modality make it hard to rely on a single modality. Thus, multimodal fusion is a practical approach...
Comparison of cognitive modeling and user performance analysis for touch screen mobile interface design Ocak, Nihan; Çağıltay, Kürşat; Department of Information Systems (2014) The main aim of this thesis is to analyze and comparatively evaluate the usability of touch screen mobile applications through cognitive modeling and end-user usability testing. The study investigates the accuracy of the estimated results cognitive model produces for touch screen mobile phone interfaces. CogTool application was used as the cognitive modeling method. Turkcell Cüzdan application, which is suitable for the implementation of both methods, was chosen as the mobile application. Based on the feedb...
Methods for location prediction of mobile phone users Keleş, İlkcan; Toroslu, İsmail Hakkı; Department of Computer Engineering (2014) Due to the increasing use of mobile phones and their increasing capabilities, huge amount of usage and location data can be collected. Location prediction is an important task for mobile phone operators and smart city administrations to provide better services and recommendations. In this work, we have investigated several approaches for location prediction problem including clustering, classification and sequential pattern mining. We propose a sequence mining based approach for location prediction of mobil...

Citation Formats

S. Gonul, T. Namli, M. Baskaya, A. A. Sinaci, A. Coşar, and İ. H. Toroslu, “Optimization of Just-in-Time Adaptive Interventions Using Reinforcement Learning,” 2018, vol. 10868, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/56210.