An Online Minimax Optimal Algorithm for Adversarial Multiarmed Bandit Problem
Sign Up to like & getrecommendations! Published in 2018 at "IEEE Transactions on Neural Networks and Learning Systems"
DOI: 10.1109/tnnls.2018.2806006
Abstract: We investigate the adversarial multiarmed bandit problem and introduce an online algorithm that asymptotically achieves the performance of the best switching bandit arm selection strategy. Our algorithms are truly online such that we do not… read more here.
Keywords: bandit; adversarial multiarmed; bandit arm; minimax optimal ... See more keywords
Multiarmed Bandit Algorithms on Zynq System-on-Chip: Go Frequentist or Bayesian?
Sign Up to like & getrecommendations! Published in 2022 at "IEEE transactions on neural networks and learning systems"
DOI: 10.1109/tnnls.2022.3190509
Abstract: Multiarmed Bandit (MAB) algorithms identify the best arm among multiple arms via exploration-exploitation trade-off without prior knowledge of arm statistics. Their usefulness in wireless radio, Internet of Things (IoT), and robotics demand deployment on edge… read more here.
Keywords: mab; algorithms; system chip; multiarmed bandit ... See more keywords
The Recommending Agricultural Product Sales Promotion Mode in E-Commerce Using Reinforcement Learning with Contextual Multiarmed Bandit Algorithms
Sign Up to like & getrecommendations! Published in 2020 at "Mathematical Problems in Engineering"
DOI: 10.1155/2020/8836000
Abstract: In recent years, sales of agricultural products in Taiwan have been transformed into electronic marketing, and agricultural products with better consumer orientation have been recommended, and farmers’ income has been improved through sales websites. In… read more here.
Keywords: multiarmed bandit; contextual multiarmed; bandit algorithms; reinforcement learning ... See more keywords