Decentralized Multi-player Multi-armed Bandits with No Collision Information
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Abstract (arXiv)
The decentralized stochastic multi-player multi-armed bandit (MP-MAB) problem, where the collision information is not available to the players, is studied in this paper. Building on the seminal work of Boursier and Perchet (2019), we propose error correction synchronization involving communication (EC-SIC), whose regret is shown to approach that of the centralized stochastic MP-MAB with collision information. By recognizing that the communication phase without collision information corresponds to the Z-channel model in information theory, the proposed EC-SIC algorithm applies optimal error correction coding for the communication of reward statistics. A fixed message length, as opposed to the logarithmically growing one in Boursier and Perchet (2019), also plays a crucial role in controlling the communication loss. Experiments with practical Z-channel codes, such as repetition code, flip code and modified Hamming code, demonstrate the superiority of EC-SIC in both synthetic and real-world datasets.
Key facts. Cited by 25 papers in the map (data through 7 Oct 2026). First posted on arXiv 29 Feb 2020.
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Citing papers per year: 2021: 10; 2022: 4; 2023: 6; 2024: 3; 2025: 1; 2026: 1.
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- 2021Federated Multi-armed Bandits with Personalizationcited by 62
- 2021Federated Linear Contextual Banditscited by 61
- 2021Federated Multi-Armed Banditscited by 59
- 2021Heterogeneous Multi-player Multi-armed Bandits: Closing the Gap and Generalizationcited by 18
- 2022A survey on multi-player banditscited by 18
- 2021Online Learning for Cooperative Multi-Player Multi-Armed Banditscited by 12
- 2021Towards Optimal Algorithms for Multi-Player Bandits without Collision Sensing Informationcited by 11
- 2021Multi-player Multi-armed Bandits with Collision-Dependent Reward Distributionscited by 8
- 2023Optimal Cooperative Multiplayer Learning Bandits with Noisy Rewards and No Communicationcited by 8
- 2021An Instance-Dependent Analysis for the Cooperative Multi-Player Multi-Armed Banditcited by 6
- 2023Competing for Shareable Arms in Multi-Player Multi-Armed Banditscited by 6
- 2021Cooperative Stochastic Multi-agent Multi-armed Bandits Robust to Adversarial Corruptionscited by 5
13 more
- 2023Incentivized Communication for Federated Banditscited by 3
- 2021A High Performance, Low Complexity Algorithm for Multi-Player Bandits Without Collision Sensing Informationcited by 2
- 2022Decentralized Stochastic Multi-Player Multi-Armed Walking Banditscited by 2
- 2024Incentivized Truthful Communication for Federated Banditscited by 2
- 2022The Pareto Frontier of Instance-Dependent Guarantees in Multi-Player Multi-Armed Bandits with no Communicationcited by 1
- 2022Multi-Player Bandits Robust to Adversarial Collisionscited by 1
- 2023Finite-Time Frequentist Regret Bounds of Multi-Agent Thompson Sampling on Sparse Hypergraphscited by 1
- 2023Harnessing the Power of Federated Learning in Federated Contextual Banditscited by 1
- 2023Constant or logarithmic regret in asynchronous multiplayer banditscited by 0
- 2024PPA-Game: Characterizing and Learning Competitive Dynamics Among Online Content Creatorscited by 0
- 2024Multi-agent Multi-armed Bandits with Stochastic Sharable Arm Capacitiescited by 0
- 2025Decentralized Asynchronous Multi-player Banditscited by 0
- 2026The Price of Decentralization in Top-K Arm Identificationcited by 0
- 2026The Price of Decentralization in Top-K Arm Identification22 Aug 2026
- 2025Decentralized Asynchronous Multi-player Bandits30 Sep 2025
- 2024Multi-agent Multi-armed Bandits with Stochastic Sharable Arm Capacities20 Aug 2024
- 2024PPA-Game: Characterizing and Learning Competitive Dynamics Among Online Content Creators22 Mar 2024
- 2024Incentivized Truthful Communication for Federated Bandits7 Feb 2024
- 2023Harnessing the Power of Federated Learning in Federated Contextual Bandits26 Dec 2023
- 2023Finite-Time Frequentist Regret Bounds of Multi-Agent Thompson Sampling on Sparse Hypergraphs24 Dec 2023
- 2023Optimal Cooperative Multiplayer Learning Bandits with Noisy Rewards and No Communication10 Nov 2023
- 2023Incentivized Communication for Federated Bandits21 Sep 2023
- 2023Constant or logarithmic regret in asynchronous multiplayer bandits31 May 2023
- 2023Competing for Shareable Arms in Multi-Player Multi-Armed Bandits30 May 2023
- 2022Decentralized Stochastic Multi-Player Multi-Armed Walking Bandits12 Dec 2022
13 more
- 2022A survey on multi-player bandits29 Nov 2022
- 2022Multi-Player Bandits Robust to Adversarial Collisions15 Nov 2022
- 2022The Pareto Frontier of Instance-Dependent Guarantees in Multi-Player Multi-Armed Bandits with no Communication19 Feb 2022
- 2021An Instance-Dependent Analysis for the Cooperative Multi-Player Multi-Armed Bandit8 Nov 2021
- 2021Heterogeneous Multi-player Multi-armed Bandits: Closing the Gap and Generalization27 Oct 2021
- 2021Federated Linear Contextual Bandits27 Oct 2021
- 2021Online Learning for Cooperative Multi-Player Multi-Armed Bandits7 Sep 2021
- 2021Multi-player Multi-armed Bandits with Collision-Dependent Reward Distributions25 Jun 2021
- 2021Cooperative Stochastic Multi-agent Multi-armed Bandits Robust to Adversarial Corruptions8 Jun 2021
- 2021Towards Optimal Algorithms for Multi-Player Bandits without Collision Sensing Information24 Mar 2021
- 2021Federated Multi-armed Bandits with Personalization25 Feb 2021
- 2021A High Performance, Low Complexity Algorithm for Multi-Player Bandits Without Collision Sensing Information19 Feb 2021
- 2021Federated Multi-Armed Bandits28 Jan 2021
- 2021Federated Multi-armed Bandits with Personalizationcited by 62
- 2021Federated Linear Contextual Banditscited by 61
- 2021Federated Multi-Armed Banditscited by 59
- 2021Heterogeneous Multi-player Multi-armed Bandits: Closing the Gap and Generalizationcited by 18
- 2022A survey on multi-player banditscited by 18
- 2021Online Learning for Cooperative Multi-Player Multi-Armed Banditscited by 12
- 2021Towards Optimal Algorithms for Multi-Player Bandits without Collision Sensing Informationcited by 11
- 2021Multi-player Multi-armed Bandits with Collision-Dependent Reward Distributionscited by 8
- 2023Optimal Cooperative Multiplayer Learning Bandits with Noisy Rewards and No Communicationcited by 8
- 2021An Instance-Dependent Analysis for the Cooperative Multi-Player Multi-Armed Banditcited by 6
- 2023Competing for Shareable Arms in Multi-Player Multi-Armed Banditscited by 6
- 2021Cooperative Stochastic Multi-agent Multi-armed Bandits Robust to Adversarial Corruptionscited by 5
12 most cited of 25 All 25 (JSON)
- 2026The Price of Decentralization in Top-K Arm Identification22 Aug 2026
- 2025Decentralized Asynchronous Multi-player Bandits30 Sep 2025
- 2024Multi-agent Multi-armed Bandits with Stochastic Sharable Arm Capacities20 Aug 2024
- 2024PPA-Game: Characterizing and Learning Competitive Dynamics Among Online Content Creators22 Mar 2024
- 2024Incentivized Truthful Communication for Federated Bandits7 Feb 2024
- 2023Harnessing the Power of Federated Learning in Federated Contextual Bandits26 Dec 2023
- 2023Finite-Time Frequentist Regret Bounds of Multi-Agent Thompson Sampling on Sparse Hypergraphs24 Dec 2023
- 2023Optimal Cooperative Multiplayer Learning Bandits with Noisy Rewards and No Communication10 Nov 2023
- 2023Incentivized Communication for Federated Bandits21 Sep 2023
- 2023Constant or logarithmic regret in asynchronous multiplayer bandits31 May 2023
- 2023Competing for Shareable Arms in Multi-Player Multi-Armed Bandits30 May 2023
- 2022Decentralized Stochastic Multi-Player Multi-Armed Walking Bandits12 Dec 2022
12 newest of 25 All 25 (JSON)