Results 61 to 70 of about 3,478,919 (201)

Active Inference-Driven Multi-Armed Bandits: Superior Performance through Dynamic Correlation Adjustments [PDF]

ITM Web of Conferences
In recent years, Multi-Armed Bandit (MAB) algorithms have gained substantial attention due to their effectiveness in real-world applications, such as recommendation systems, autonomous systems, and dynamic resource allocation. Traditional MAB algorithms,
Lin Xiaoqi
doaj   +1 more source

Computational Modeling of Decision Making Enhances the Adversity Researcher's Toolbox

Topics in Cognitive Science, EarlyView.
Abstract Over the past decades, there has been major progress in our understanding of how adversity influences cognitive abilities and strategies. However, most of this research is based on raw performance, such as response times and accuracy. These measures are informative about decision‐making outcomes but tell us little about cognitive processes. In
Stefan Vermeent, Anna‐Lena Schubert, Willem E. Frankenhuis   +2 more
wiley   +1 more source

Selective Reviews of Bandit Problems in AI via a Statistical View

Mathematics
Reinforcement Learning (RL) is a widely researched area in artificial intelligence that focuses on teaching agents decision-making through interactions with their environment.
Pengjie Zhou, Haoyu Wei, Huiming Zhang
doaj   +1 more source

A dynamic distributed energy storage control strategy for providing primary frequency regulation using multi‐armed bandits method

IET Generation, Transmission & Distribution, 2022
Maintaining frequency stability is a crucial but challenging task for the stable operation of a power system. The distributed energy storage (DES) can charge or discharge for both upward and downward frequency regulation, exploring and effectively using ...
Jianfeng Sun, Yuan Zhao, Nianchu Zhang, Xinyi Chen, Qinran Hu, Jieying Song   +5 more
doaj   +1 more source

A Comprehensive Review on Federated and Incremental Learning in Spatial Crowdsourcing Systems

WIREs Data Mining and Knowledge Discovery, Volume 16, Issue 4, December 2026.
A comprehensive overview of Federated and Incremental Learning (FIL) integration in Spatial Crowdsourcing, highlighting privacy, security, adaptability, efficiency challenges, and future research directions. ABSTRACT Spatial Crowdsourcing (SC) coordinates workers and requesters through personal mobile devices to complete location‐dependent tasks in ...
Md Mujibur Rahman, Quazi Mamun, Michael Bewong, Md Zahidul Islam   +3 more
wiley   +1 more source

Pruning neural networks using multi-armed bandits [PDF]

, 2020
The successful application of deep learning has led to increasing expectationsof their use in embedded systems. This in turn, has created the need to findways of reducing the size of neural networks.
Ameen, SA, Vadera, S
core   +1 more source

Compositional generalization in multi-armed bandits

, 2021
To what extent do human reward learning and decision-making rely on the ability to represent and generate richly structured relationships between options? We provide evidence that structure learning and the principle of compositionality play crucial roles in human reinforcement learning.
Saanum, Tankred, Schulz, Eric, Speekenbrink, Maarten   +2 more
openaire   +5 more sources

Knapsack based optimal policies for budget-limited multi-armed bandits

, 2012
In budget-limited multi-armed bandit (MAB) problems, the learner’s actions are costly and constrained by a fixed budget. Consequently, an optimal exploitation policy may not be to pull the optimal arm repeatedly, as is the case in other variants of MAB ...
Tran-Thanh, Long, Jennings, Nicholas R., Jennings, Nicholas R, Chapman, Archie, Rogers, Alex   +4 more
core   +1 more source

One-Bit Feedback Exponential Learning for Beam Alignment in Mobile mmWave

IEEE Access, 2020
Efficient beam alignment in wireless networks capable of supporting device mobility is currently one of the major challenges in mmWave communications. In this context, we formulate the beam-alignment problem via the adversarial multi-armed bandit (MAB ...
Irched Chafaa, E. Veronica Belmega, Merouane Debbah   +2 more
doaj   +1 more source

Deepening the real options debate: Real options as dynamic optimization

Strategic Management Journal, Volume 47, Issue 11, Page 2823-2870, November 2026.
Abstract Research Summary Is real option theory useful for management research? This topic was hotly debated two decades ago. Real options were said to be inapplicable to management research and to lack conceptual distinctiveness. Whereas responses to the claim about the non‐distinctiveness of real options were disparate, the concern about the theory's
Arkadiy V. Sakhartov, Joseph T. Mahoney, Jeffrey J. Reuer   +2 more
wiley   +1 more source