Ontology type: schema:Chapter
2018-05-30
AUTHORSSuat Gonul , Tuncay Namli , Mert Baskaya , Ali Anil Sinaci , Ahmet Cosar , Ismail Hakki Toroslu
ABSTRACTMomentary 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. More... »
PAGES334-341
Recent Trends and Future Technology in Applied Intelligence
ISBN
978-3-319-92057-3
978-3-319-92058-0
http://scigraph.springernature.com/pub.10.1007/978-3-319-92058-0_32
DOIhttp://dx.doi.org/10.1007/978-3-319-92058-0_32
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