Decision making for large-scale multi-armed bandit problems using bias control of chaotic temporal waveforms in semiconductor lasers [PDF]
Scientific Reports, 2022 Decision making using photonic technologies has been intensively researched for solving the multi-armed bandit problem, which is fundamental to reinforcement learning.
Kensei Morijiri +4 more
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Some performance considerations when using multi-armed bandit algorithms in the presence of missing data. [PDF]
PLoS ONE, 2022 When comparing the performance of multi-armed bandit algorithms, the potential impact of missing data is often overlooked. In practice, it also affects their implementation where the simplest approach to overcome this is to continue to sample according ...
Xijin Chen +3 more
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Re-Learning EXP3 Multi-Armed Bandit Algorithm for Enhancing the Massive IoT-LoRaWAN Network Performance [PDF]
Sensors, 2022 Long-Range Wide Area Network (LoRaWAN) is an open-source protocol for the standard Internet of Things (IoT) Low Power Wide Area Network (LPWAN). This work’s focal point is the LoRa Multi-Armed Bandit decentralized decision-making solution.
Samar Adel Almarzoqi +3 more
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Applied Sciences, 2022 In recent times, the number of Internet of Things devices has increased considerably. Numerous Internet of Things devices generate enormous traffic, thereby causing network congestion and packet loss.
So Hasegawa +6 more
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Monte Carlo elites: quality-diversity selection as a multi-armed bandit problem [PDF]
Annual Conference on Genetic and Evolutionary Computation, 2021 A core challenge of evolutionary search is the need to balance between exploration of the search space and exploitation of highly fit regions. Quality-diversity search has explicitly walked this tightrope between a population's diversity and its quality.
Konstantinos Sfikas +2 more
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Risk-aware multi-armed bandit problem with application to portfolio selection [PDF]
Royal Society Open Science, 2017 Sequential portfolio selection has attracted increasing interest in the machine learning and quantitative finance communities in recent years. As a mathematical framework for reinforcement learning policies, the stochastic multi-armed bandit problem ...
Xiaoguang Huo, Feng Fu
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Multi-Armed Bandit-Based User Network Node Selection [PDF]
SensorsIn the scenario of an integrated space–air–ground emergency communication network, users encounter the challenge of rapidly identifying the optimal network node amidst the uncertainty and stochastic fluctuations of network states. This study introduces a
Qinyan Gao, Zhidong Xie
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Journal of Modern Power Systems and Clean Energy, 2020 As the penetration of renewable energy continues to increase, stochastic and intermittent generation resources gradually replace the conventional generators, bringing significant challenges in stabilizing power system frequency.
Xinyi Chen +5 more
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Optimizing Station-Based Shared E-Bike Allocation Using Multi-Armed Bandit Algorithms [PDF]
ITM Web of ConferencesIn the era of rapid urban transformation, the sharing economy has revolutionized transportation solutions, with shared bicycles emerging as a prominent example.
Zhao Wenkui
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Multi-objective contextual bandits in recommendation systems for smart tourism [PDF]
Scientific ReportsIn the context of smart tourism, recommender systems play a pivotal role in enhancing the personalization and quality of travel experiences. Tourists often face challenges in decision-making due to information overload.
Sara Qassimi, Said Rakrak
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