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Related papers: Multi-player Bandits for Distributed Cognitive Rad…

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We consider the problem of distributed online learning with multiple players in multi-armed bandits (MAB) models. Each player can pick among multiple arms. When a player picks an arm, it gets a reward. We consider both i.i.d. reward model…

Optimization and Control · Mathematics 2016-11-18 Dileep Kalathil , Naumaan Nayyar , Rahul Jain

This paper deals with the problem of efficient resource allocation in dynamic infrastructureless wireless networks. Assuming a reactive interference-limited scenario, each transmitter is allowed to select one frequency channel (from a…

Computer Science and Game Theory · Computer Science 2015-02-13 Setareh Maghsudi , Slawomir Stanczak

We study a distributed decision-making problem in which multiple agents face the same multi-armed bandit (MAB), and each agent makes sequential choices among arms to maximize its own individual reward. The agents cooperate by sharing their…

Optimization and Control · Mathematics 2020-08-13 Peter Landgren , Vaibhav Srivastava , Naomi Ehrich Leonard

A sequential decision process in which an adaptive radar system repeatedly interacts with a finite-state target channel is studied. The radar is capable of passively sensing the spectrum at regular intervals, which provides side information…

Information Theory · Computer Science 2021-10-15 Charles E. Thornton , R. Michael Buehrer , Anthony F. Martone

We formulate and study a decentralized multi-armed bandit (MAB) problem. There are M distributed players competing for N independent arms. Each arm, when played, offers i.i.d. reward according to a distribution with an unknown parameter. At…

Optimization and Control · Mathematics 2015-05-14 Keqin Liu , Qing Zhao

Multi-arm bandit (MAB) algorithms have been used to learn optimal beams for millimeter wave communication systems. Here, the complexity of learning the optimal beam linearly scales with the number of beams, leading to high latency when…

Signal Processing · Electrical Eng. & Systems 2023-06-30 Akanksha Sneh , Sumit Darak , Shobha Sundar Ram , Manjesh Hanawal

We study two-sided matching markets in which one side of the market (the players) does not have a priori knowledge about its preferences for the other side (the arms) and is required to learn its preferences from experience. Also, we assume…

Machine Learning · Computer Science 2021-06-23 Lydia T. Liu , Feng Ruan , Horia Mania , Michael I. Jordan

A stochastic multi-user multi-armed bandit framework is used to develop algorithms for uncoordinated spectrum access. In contrast to prior work, it is assumed that rewards can be non-zero even under collisions, thus allowing for the number…

Information Theory · Computer Science 2021-01-13 Meghana Bande , Akshayaa Magesh , Venugopal V. Veeravalli

Data traffic demand in cellular networks has been tremendously growing and has led to creating congested RF environment. Accordingly, innovative approaches for spectrum sharing have been proposed and implemented to accommodate several…

Signal Processing · Electrical Eng. & Systems 2017-09-26 Mina Labib , Vuk Marojevic , Anthony F. Martone , Jeffrey H. Reed , Amir I. Zaghloul

New generation of radar systems will need to coexist with other radio frequency (RF) systems, anticipating their behavior and reacting appropriately to avoid interference. In light of this requirement, this paper designs, implements, and…

Signal Processing · Electrical Eng. & Systems 2021-03-23 Mohammad Alaee-Kerahroodi , Ehsan Raei , Sumit Kumar , Bhavani Shankar Mysore Rama Rao

The focus of this study is on the spectrum sharing between multiple-input multiple-output (MIMO) communications and co-located MIMO radar systems in multi-path environments. The major challenge is to suppress the mutual interference between…

Information Theory · Computer Science 2023-04-11 Haoyu Zhang , Li Chen , Kaifeng Han , Yunfei Chen , Guo Wei

Various approaches have emerged for multi-armed bandits in distributed systems. The multiplayer dueling bandit problem, common in scenarios with only preference-based information like human feedback, introduces challenges related to…

Machine Learning · Computer Science 2025-04-24 Or Raveh , Junya Honda , Masashi Sugiyama

Multi-player multi-armed bandit is an increasingly relevant decision-making problem, motivated by applications to cognitive radio systems. Most research for this problem focuses exclusively on the settings that players have \textit{full…

Machine Learning · Computer Science 2022-12-14 Guojun Xiong , Jian Li

Increased amounts of bandwidth are required to guarantee both high-quality/high-rate wireless services (4G and 5G) and reliable sensing capabilities such as automotive radar, air traffic control, earth geophysical monitoring and security…

Signal Processing · Electrical Eng. & Systems 2019-02-26 Le Zheng , Marco Lops , Yonina C. Eldar , Xiaodong Wang

We consider the distributed channel selection problem in the context of device-to-device (D2D) communication as an underlay to a cellular network. Underlaid D2D users communicate directly by utilizing the cellular spectrum but their…

Computer Science and Game Theory · Computer Science 2015-02-13 Setareh Maghsudi , Slawomir Stanczak

Multi-Armed Bandit (MAB) systems are witnessing an upswing in applications within multi-agent distributed environments, leading to the advancement of collaborative MAB algorithms. In such settings, communication between agents executing…

Machine Learning · Computer Science 2024-04-30 Osama A. Hanna , Merve Karakas , Lin F. Yang , Christina Fragouli

Modern radars often adopt multi-carrier waveform which has been widely discussed in the literature. However, with the development of civil communication, more and more spectrum resource has been occupied by communication networks. Thus,…

Signal Processing · Electrical Eng. & Systems 2022-12-26 Zhao Shan , Lei Wang , Pengfei Liu , Tianyao Huang , Yimin Liu

Device-to-device (D2D) communications is expected to play a significant role in increasing the system capacity of the fifth generation (5G) wireless networks. To accomplish this, efficient power and resource allocation algorithms need to be…

Networking and Internet Architecture · Computer Science 2019-01-01 Anushree Neogi , Prasanna Chaporkar , Abhay Karandikar

We study distributed cooperative decision-making under the explore-exploit tradeoff in the multiarmed bandit (MAB) problem. We extend the state-of-the-art frequentist and Bayesian algorithms for single-agent MAB problems to cooperative…

Systems and Control · Computer Science 2019-09-18 Peter Landgren , Vaibhav Srivastava , Naomi Ehrich Leonard

For a wireless avionics communication system, a Multi-arm bandit game is mathematically formulated, which includes channel states, strategies, and rewards. The simple case includes only two agents sharing the spectrum which is fully studied…

Signal Processing · Electrical Eng. & Systems 2017-11-15 Jingyang Lu , Lun Li , Dan Shen , Genshe Chen , Bin Jia , Erik Blasch , Khanh Pham