Computer ScienceScientific Reports
Exploring optimal control of epidemic spread using reinforcement learning
A. Q. Ohi, M. F. Mridha, et al.
This research by Abu Quwsar Ohi, M. F. Mridha, Muhammad Mostafa Monowar, and Md. Abdul Hamid delves into harnessing reinforcement learning to tackle pandemic control strategies, balancing health and economic impacts during crises reminiscent of COVID-19.
Related Publications
Explore these studies to deepen your understanding
Adjacent work that informs or extends this paper's methodology and findings.
Business
Decoding consumer purchase decisions: exploring the predictive power of EEG features in online shopping environments using machine learning
Z. Xu and S. Liu
Chemistry
AlphaFlow: autonomous discovery and optimization of multi-step chemistry using a self-driven fluidic lab guided by reinforcement learning
A. A. Volk, R. W. Epps, et al.
Biology
Revealing principles of autonomous thermal soaring in windy conditions using vulture-inspired deep reinforcement-learning
Y. Flato, R. Harel, et al.
Engineering and Technology
Wing-strain-based flight control of flapping-wing drones through reinforcement learning
T. Kim, I. Hong, et al.
