982
Views
0
CrossRef citations to date
0
Altmetric
Research Article

Personalized control system via reinforcement learning: maximizing utility based on user ratings

&
Pages 18-26 | Received 08 Sep 2022, Accepted 27 Dec 2022, Published online: 21 Jan 2023

References

  • Fan H, Poole MS. What is personalization? Perspectives on the design and implementation of personalization in information systems. J Organ Comput Electron Commer. 2006;16(3–4):179–202.
  • Tuzhilin A. Personalization: the state of the art and future directions. Bus Comput. 2009;3(3):3–43.
  • Hasenjager M, Heckmann M, Wersing H. A survey of personalization for advanced driver assistance systems. IEEE Trans Intell Veh. 2020;5(2):335–344.
  • Yi D, Su J, Hu L, et al. Implicit personalization in driving assistance: state-of-the-art and open issues. IEEE Trans Intell Veh. 2019;5(3):397–413.
  • Lu C, Gong J, Lv C, et al. A personalized behavior learning system for human-like longitudinal speed control of autonomous vehicles. Sensors. 2019;19(17):3672.
  • Noto N, Okuda H, Tazaki Y, et al. Steering assisting system for obstacle avoidance based on personalized potential field. In: 2012 15th International IEEE Conference on Intelligent Transportation Systems. IEEE; 2012. p. 1702–1707.
  • Wiering MA, Van Otterlo M. Reinforcement learning. Adapt Learn Optim. 2012;12(3):729.
  • Lewis FL, Vrabie D, Vamvoudakis KG. Reinforcement learning and feedback control: using natural decision methods to design optimal adaptive controllers. IEEE Contr Syst Mag. 2012;32(6):76–105.
  • Kiumarsi B, Vamvoudakis KG, Modares H, et al. Optimal and autonomous control using reinforcement learning: a survey. IEEE Trans Neural Netw Learn Syst. 2018;29(6):2042–2062.
  • Zanon M, Gros S, Bemporad A. Practical reinforcement learning of stabilizing economic MPC. In: 2019 18th European Control Conference (ECC), Naples; 2019. p. 2258–2263.
  • Ernst D, Glavic M, Capitanescu F, et al. Reinforcement learning versus model predictive control: a comparison on a power system problem. IEEE Trans Syst Man Cybern B. 2009;39(2):517–529.
  • Ng AY, Russell S. Algorithms for inverse reinforcement learning. In: International Conference on Machine Learning, Stanford, CA; Vol. 1; 2000. p. 2.
  • Arora S, Doshi P. A survey of inverse reinforcement learning: challenges, methods and progress. Artif Intell. 2021;297:Article ID 103500.
  • Ozkan MF, Ma Y. Modeling driver behavior in car-following interactions with automated and human-driven vehicles and energy efficiency evaluation. IEEE Access. 2021;9:64696–64707.
  • Ozkan MF, Rocque AJ, Ma Y. Inverse reinforcement learning based stochastic driver behavior learning. IFAC-PapersOnLine. 2021;54(20):882–888.
  • Ozkan MF, Ma Y. Personalized adaptive cruise control and impacts on mixed traffic. In: 2021 American Control Conference (ACC), New Orleans; 2021. p. 412–417.
  • Milanese M, Vicino A. Optimal estimation theory for dynamic systems with set membership uncertainty: an overview. Automatica. 1991;27(6):997–1009.
  • Savkin AV, Petersen IR. Set-valued state estimation via a limited capacity communication channel. IEEE Trans Automat Contr. 2003;48(4):676–680.
  • Shi D, Chen T, Shi L. On set-valued kalman filtering and its application to event-based state estimation. IEEE Trans Automat Control. 2015;60(5):1275–1290.