Results 41 to 50 of about 33,931 (272)
Collaborative Multi-Agent Multi-Armed Bandit Learning for Small-Cell Caching [PDF]
IEEE Transactions on Wireless Communications, 2020 This paper investigates learning-based caching in small-cell networks (SCNs) when user preference is unknown. The goal is to optimize the cache placement in each small base station (SBS) for minimizing the system long-term transmission delay.
Xianzhe Xu, M. Tao, Cong Shen
semanticscholar +1 more source
Finding structure in multi-armed bandits [PDF]
Cognitive Psychology, 2018 AbstractHow do humans search for rewards? This question is commonly studied using multi-armed bandit tasks, which require participants to trade off exploration and exploitation. Standard multi-armed bandits assume that each option has an independent reward distribution.
Schulz, Eric +2 more
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Multi-armed bandits for performance marketing
International Journal of Data Science and Analytics, 2023 Abstract This paper deals with the problem of optimising bids and budgets of a set of digital advertising campaigns. We improve on the current state of the art by introducing support for multi-ad group marketing campaigns and developing a highly data efficient parametric contextual bandit.
Gigli, M, Stella, F
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Performance of Multi-Armed Bandit Algorithms in Dynamic vs. Static Environments: A Comparative Analysis [PDF]
ITM Web of ConferencesThis paper conducts a comparative analysis of Multi-Armed Bandit (MAB) algorithms, particularly the Upper Confidence Bound (UCB) and Thompson Sampling (TS) algorithms, and focuses on the performance of these algorithms in both static and dynamic ...
Zhao Boxi
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Multi-armed bandits with dependent arms
Machine Learning, 2023 We study a variant of the classical multi-armed bandit problem (MABP) which we call as Multi-Armed Bandits with dependent arms. More specifically, multiple arms are grouped together to form a cluster, and the reward distributions of arms belonging to the same cluster are known functions of an unknown parameter that is a characteristic of the cluster ...
Rahul Singh +3 more
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Multi-Armed Bandits and Quantum Channel Oracles [PDF]
QuantumMulti-armed bandits are one of the theoretical pillars of reinforcement learning. Recently, the investigation of quantum algorithms for multi-armed bandit problems was started, and it was found that a quadratic speed-up (in query complexity) is possible ...
Simon Buchholz +2 more
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Differential Privacy in Social Networks Using Multi-Armed Bandit
IEEE Access, 2022 There has been an exponential growth over the years in the number of users connected to social networks. This has spurred research interest in social networks to ensure the privacy of users. From a theoretical standpoint, a social network is modeled as a
Olusola T. Odeyomi
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Characterizing Truthful Multi-armed Bandit Mechanisms [PDF]
SIAM Journal on Computing, 2014 This is the full version of a conference paper published in ACM EC 2009. This revision is re-focused to emphasize the results that do not rely on the "IIA assumption" (see the paper for the definition)
Babaioff, Moshe +2 more
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A Change-Detection based Framework for Piecewise-stationary Multi-Armed Bandit Problem [PDF]
AAAI Conference on Artificial Intelligence, 2017 The multi-armed bandit problem has been extensively studied under the stationary assumption. However in reality, this assumption often does not hold because the distributions of rewards themselves may change over time.
Fang Liu, Joohyung Lee, N. Shroff
semanticscholar +1 more source
Addictive Games: Case Study on Multi-Armed Bandit Game
Information, 2021 The attraction of games comes from the player being able to have fun in games. Gambling games that are based on the Variable-Ratio schedule in Skinner’s experiment are the most typical addictive games.
Xiaohan Kang +3 more
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