Results 21 to 30 of about 33,931 (272)
Multi-Access Communications With Energy Harvesting: A Multi-Armed Bandit Model and the Optimality of the Myopic Policy [PDF]
IEEE Journal on Selected Areas in Communications, 2015 Deniz Gunduz
exaly +2 more sources
Adversarially Robust Multi-Armed Bandit Algorithm with Variance-Dependent Regret Bounds [PDF]
Annual Conference Computational Learning Theory, 2022 This paper considers the multi-armed bandit (MAB) problem and provides a new best-of-both-worlds (BOBW) algorithm that works nearly optimally in both stochastic and adversarial settings. In stochastic settings, some existing BOBW algorithms achieve tight
Shinji Ito, Taira Tsuchiya, J. Honda
semanticscholar +1 more source
BandMaxSAT: A Local Search MaxSAT Solver with Multi-armed Bandit [PDF]
International Joint Conference on Artificial Intelligence, 2022 We address Partial MaxSAT (PMS) and Weighted PMS (WPMS), two practical generalizations of the MaxSAT problem, and propose a local search algorithm called BandMaxSAT, that applies a multi-armed bandit to guide the search direction, for these problems. The
Jiongzhi Zheng +5 more
semanticscholar +1 more source
Pareto Regret Analyses in Multi-objective Multi-armed Bandit [PDF]
International Conference on Machine Learning, 2022 We study Pareto optimality in multi-objective multi-armed bandit by providing a formulation of adversarial multi-objective multi-armed bandit and defining its Pareto regrets that can be applied to both stochastic and adversarial settings.
Mengfan Xu, D. Klabjan
semanticscholar +1 more source
Design of Multi-Armed Bandit-Based Routing for in-Network Caching
IEEE Access, 2023 This paper proposes a multi-armed bandit-based routing method for in-network cache-enabled networks. In-network caching enables intermediate routers to store contents in their cache, which is adopted in new networking paradigms such as Information ...
Gen Tabei +3 more
doaj +1 more source
LLM-Informed Multi-Armed Bandit Strategies for Non-Stationary Environments
Electronics, 2023 In this paper, we introduce an innovative approach to handling the multi-armed bandit (MAB) problem in non-stationary environments, harnessing the predictive power of large language models (LLMs).
J. de Curtò +5 more
semanticscholar +1 more source
Learning the Truth in Social Networks Using Multi-Armed Bandit
IEEE Access, 2020 This paper explains how agents in a social network can learn the arbitrary time-varying true state of the network. This is practical in social networks where information is released and updated without any coordination.
Olusola T. Odeyomi
doaj +1 more source
QoS-Aware Multi-armed Bandits [PDF]
2016 IEEE 1st International Workshops on Foundations and Applications of Self* Systems (FAS*W), 2016 Motivated by runtime verification of QoS requirements in self-adaptive and self-organizing systems that are able to reconfigure their structure and behavior in response to runtime data, we propose a QoS-aware variant of Thompson sampling for multi-armed bandits.
Belzner, Lenz, Gabor, Thomas
openaire +2 more sources
Multi-Armed Bandits With Correlated Arms [PDF]
IEEE Transactions on Information Theory, 2021 We consider a multi-armed bandit framework where the rewards obtained by pulling different arms are correlated. We develop a unified approach to leverage these reward correlations and present fundamental generalizations of classic bandit algorithms to the correlated setting.
Samarth Gupta +3 more
openaire +2 more sources
Beta Upper Confidence Bound Policy for the Design of Clinical Trials
Austrian Journal of Statistics, 2023 The multi-armed bandit problem is a classic example of the exploration-exploitation trade-off well suited to model sequential resource allocation under uncertainty.
Andrii Dzhoha, Iryna Rozora
doaj +1 more source