Results 111 to 120 of about 3,478,919 (201)

Global Rewards in Restless Multi-Armed Bandits [PDF]

Restless multi-armed bandits (RMAB) extend multi-armed bandits so pulling an arm impacts future states. Despite the success of RMABs, a key limiting assumption is the separability of rewards into a sum across arms. We address this deficiency by proposing
Fang, Fei, Shi, Zheyuan Ryan, Raman, Naveen   +2 more
core   +1 more source

Communication-Efficient Collaborative Regret Minimization in Multi-Armed Bandits

In this paper, we study the collaborative learning model, which concerns the tradeoff between parallelism and communication overhead in multi-agent multi-armed bandits.
Zhang, Qin, Karpov, Nikolai
core   +1 more source

Two-stage index computation for bandits with switching penalties I : switching costs [PDF]

This paper addresses the multi-armed bandit problem with switching costs. Asawa and Teneketzis (1996) introduced an index that partly characterizes optimal policies, attaching to each bandit state a "continuation index" (its Gittins index) and a ...
Jose Nino-Mora
core  

A multi-armed bandits empowered transmission scheme for IRS-assisted MISO system

物联网学报
Intelligent reflecting surface (IRS) is an effective technology that can enhance millimeter-wave communication performance and address transmission challenges.
SONG Yunchao, LI Hao, LIANG Huibin, WANG Ge   +3 more
doaj   +2 more sources

Constrained Best Arm Identification in Grouped Bandits

IEEE Access
We study a grouped bandit setting where each arm comprises multiple independent sub-arms referred to as attributes. Each attribute of each arm has an independent stochastic reward.
Sahil Dharod, Malyala Preethi Sravani, Sakshi Heda, Sharayu Moharir   +3 more
doaj   +1 more source

Collaborative DNN inference in maritime edge intelligence networks with group neural multi-armed bandits

Intelligent and Converged Networks
Collaborative Deep Neural Networks (DNNs) inference has emerged as a promising paradigm for growing number of artificial intelligence-integrated maritime Internet of Things (IoT) devices in maritime edge intelligence networks.
Yulei Wang, Shishi Liu, Di Bai, Yongqiang Cui   +3 more
doaj   +1 more source

State-Separated SARSA: A Practical Sequential Decision-Making Algorithm with Recovering Rewards

Algorithms
While many multi-armed bandit algorithms assume that rewards for all arms are constant across rounds, this assumption does not hold in many real-world scenarios.
Yuto Tanimoto, Kenji Fukumizu
doaj   +1 more source

Adaptive and Explainable Test Case Prioritization in Continuous Integration: A Systematic Review of Reinforcement Learning, Learning-to-Rank, and Search-/Combinatorial-Based Methods

IEEE Access
Continuous Integration requires fast fault exposure under strict time budgets. Test case prioritization orders regression tests to expose failures early while respecting budget limits and operational constraints.
Srinivasa Rao Kongarana, Ananda Rao Akepogu, Palagiri Radhika Raju   +2 more
doaj   +1 more source

Introduction to Multi-Armed Bandits [PDF]

Multi-armed bandits a simple but very powerful framework for algorithms that make decisions over time under uncertainty. An enormous body of work has accumulated over the years, covered in several books and surveys. This book provides a more introductory,
Slivkins, Aleksandrs
core   +1 more source

A state-of-the-art survey and benchmarking of Adaptive Modulation and Coding for Underwater Acoustic Communications

Applied Ocean Research
Adaptive Modulation and Coding (AMC) is a critical technique for optimising data transmission in the highly variable and challenging domain of Underwater Acoustic Communication (UWAC).
Zachary Cooper-Baldock, Eirini Panteli, Paulo E. Santos   +2 more
doaj   +1 more source