no code implementations • 3 Jun 2023 • Jiaqi Yan, Kuo Li, Hideaki Ishii
In this paper, we study the problem of parameter estimation in a sensor network, where the measurements and updates of some sensors might be arbitrarily manipulated by adversaries.
no code implementations • 31 Oct 2021 • Kuo Li, Qing-Shan Jia
Furthermore, convergence analysis is given under the discrete-space case, which guarantees that the policy will be reinforced by alternating between the processes of policy evaluation and policy improvement.
no code implementations • 31 Oct 2021 • Kuo Li, Qing-Shan Jia, Jiaqi Yan
We formulate the sampling process as a policy searching problem and give a solution from the perspective of Reinforcement Learning (RL).