Results 171 to 180 of about 3,478,919 (201)

MAB-OS: Multi-Armed Bandits Metaheuristic Optimizer Selection

Applied Soft Computing Journal, 2022
Metaheuristic algorithms are derivative-free optimizers designed to estimate the global optima for optimization problems. Keeping balance between exploitation and exploration and the performance complementarity between the algorithms have led to the ...
Seyedali Mirjalili, Amir Barati Farimani, Kazem Meidani   +2 more
exaly   +2 more sources

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The Multi-Armed Bandit With Stochastic Plays

IEEE Transactions on Automatic Control, 2018
We extend the stochastic multi-armed bandit to the case where the number of arms to play evolves as a stationary process. Our work is motivated by demand response in power systems, in which the number of arms to play, or loads to dispatch, depends on a random power imbalance.
Antoine Lesage-Landry, Joshua A. Taylor
openaire   +3 more sources

On optimal foraging and multi-armed bandits

2013 51st Annual Allerton Conference on Communication, Control, and Computing (Allerton), 2013
We consider two variants of the standard multi-armed bandit problem, namely, the multi-armed bandit problem with transition costs and the multi-armed bandit problem on graphs. We develop block allocation algorithms for these problems that achieve an expected cumulative regret that is uniformly dominated by a logarithmic function of time, and an ...
Vaibhav Srivastava, Paul Reverdy, Naomi Ehrich Leonard   +2 more
openaire   +2 more sources

Multi-Armed Bandits With Costly Probes

IEEE Transactions on Information Theory
Multi-armed bandits is a sequential decision-making problem where an agent must choose between multiple actions to maximize its cumulative reward over time, while facing uncertainty about the rewards associated with each action. The challenge lies in balancing the exploration of potentially higher-rewarding actions with the exploitation of known high ...
Eray Can Elumar, Cem Tekin, Osman Yagan
openaire   +3 more sources

Compression for Multi-Arm Bandits

IEEE Journal on Selected Areas in Information Theory, 2022
Osama A. Hanna, Lin F. Yang, Christina Fragouli   +2 more
openaire   +2 more sources

Application of multi-armed bandits to dose-finding clinical designs

Artificial Intelligence in Medicine, 2023
Masahiro Kojima
exaly  

Efficient algorithms for multi-armed bandits with additional feedbacks: Modeling and algorithms

Information Sciences, 2023
Hong Xie, Zhi Qi
exaly  

Multi-Player Multi-Armed Bandits With Collision-Dependent Reward Distributions

IEEE Transactions on Signal Processing, 2021
Chengshuai Shi, Cong Shen
exaly  

Multi-Armed Bandits in Recommendation Systems: A survey of the state-of-the-art and future directions

Expert Systems With Applications, 2022
Leonardo Rocha, Adriano C.M. Pereira, Heitor Werneck   +2 more
exaly  

Time is Budget: A Heuristic for Reducing the Risk of Ruin in Multi-armed Gambler Bandits

Lecture Notes in Computer Science, 2022
Xavier Pucel, Jean-Loup Farges
exaly