Optimal resource allocation for AGIN 6G: a learning-based three-sided matching approach

P Qin, M Wang, Z Cai, R Ding, X Zhao… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
As ubiquitous interconnection becomes a reality for human beings, addressing the
challenge of seamless coverage in the near future 6G network, particularly for remote area …

Reinforcement learning empowered unmanned aerial vehicle assisted internet of things networks

SK Mahmud - 2023 - qmro.qmul.ac.uk
This thesis aims towards performance enhancement for unmanned aerial vehicles (UAVs)
assisted internet of things network (IoT). In this realm, novel reinforcement learning (RL) …

Dependency of regret on accuracy of variance estimation for different versions of UCB strategy for Gaussian multi-armed bandits

SV Garbar - Journal of Physics: Conference Series, 2021 - iopscience.iop.org
We consider two variations of upper confidence bound strategy for Gaussian two-armed
bandits. Rewards for the arms are assumed to have unknown expected values and …

Stochastic differential equations for limiting description of UCB rule for Gaussian multi-armed bandits

S Garbar - arxiv preprint arxiv:2112.06423, 2021 - arxiv.org
We consider the upper confidence bound strategy for Gaussian multi-armed bandits with
known control horizon sizes $ N $ and build its limiting description with a system of …

Estimation of Both Unknown Parameters in Gaussian Multi-armed Bandit for Batch Processing Scenario

S Garbar - … Conference on Mathematical Optimization Theory and …, 2023 - Springer
We consider a Gaussian multi-armed bandit problem with both reward means and variances
unknown. A Gaussian multi-armed bandit is considered because in case of batch …