Cover Image

Robust and Performance Incentivizing Algorithms for Multi-Armed Bandits with Strategic Agents

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Esmaeili, Seyed A., Shin, Suho, Slivkins, Aleksandrs
Format:	Preprint
Published:	2023
Subjects:	Computer Science and Game Theory Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Bandit Social Learning: Exploration under Myopic Behavior
by: Banihashem, Kiarash, et al.
Published: (2023)

Exploration and Persuasion
by: Slivkins, Aleksandrs
Published: (2024)

Competing Bandits: The Perils of Exploration Under Competition
by: Aridor, Guy, et al.
Published: (2020)

Incentivizing Exploration with Selective Data Disclosure
by: Immorlica, Nicole, et al.
Published: (2018)

Exploration and Incentivizing Participation in Randomized Trials
by: Li, Yingkai, et al.
Published: (2022)

Adaptive Discretization against an Adversary: Lipschitz bandits, Dynamic Pricing, and Auction Tuning
by: Podimata, Chara, et al.
Published: (2020)

Bandit Social Learning with Exploration Episodes
by: Banihashem, Kiarash, et al.
Published: (2026)

Replication-proof Bandit Mechanism Design with Bayesian Agents
by: Shin, Suho, et al.
Published: (2023)

Strategic Multi-Armed Bandit Problems Under Debt-Free Reporting
by: Yahmed, Ahmed Ben, et al.
Published: (2025)

Autobidders with Budget and ROI Constraints: Efficiency, Regret, and Pacing Dynamics
by: Lucier, Brendan, et al.
Published: (2023)

Multi-Agent Combinatorial-Multi-Armed-Bandit framework for the Submodular Welfare Problem under Bandit Feedback
by: Pokhriyal, Subham, et al.
Published: (2026)

Impact of Decentralized Learning on Player Utilities in Stackelberg Games
by: Donahue, Kate, et al.
Published: (2024)

Incentivized Learning in Principal-Agent Bandit Games
by: Scheid, Antoine, et al.
Published: (2024)

Learning to Lead: Incentivizing Strategic Agents in the Dark
by: Wu, Yuchen, et al.
Published: (2025)

Achieving PAC Guarantees in Mechanism Design through Multi-Armed Bandits
by: Osogami, Takayuki, et al.
Published: (2024)

Adversaries With Incentives: A Strategic Alternative to Adversarial Robustness
by: Ehrenberg, Maayan, et al.
Published: (2024)

Incentivized Truthful Communication for Federated Bandits
by: Wei, Zhepei, et al.
Published: (2024)

Incentive-compatible Bandits: Importance Weighting No More
by: Zimmert, Julian, et al.
Published: (2024)

Introduction to Multi-Armed Bandits
by: Slivkins, Aleksandrs
Published: (2019)

Strategic Linear Contextual Bandits
by: Buening, Thomas Kleine, et al.
Published: (2024)

Improved Bandits in Many-to-one Matching Markets with Incentive Compatibility
by: Kong, Fang, et al.
Published: (2024)

Gradient Manipulation in Distributed Stochastic Gradient Descent with Strategic Agents: Truthful Incentives with Convergence Guarantees
by: Chen, Ziqin, et al.
Published: (2026)

Regret Analysis of Repeated Delegated Choice
by: Hajiaghayi, MohammadTaghi, et al.
Published: (2023)

Strategic Incentivization for Locally Differentially Private Federated Learning
by: Pagoti, Yashwant Krishna, et al.
Published: (2025)

Leaderboard Incentives: Model Rankings under Strategic Post-Training
by: Chen, Yatong, et al.
Published: (2026)

Strategically-Robust Learning Algorithms for Bidding in First-Price Auctions
by: Kumar, Rachitesh, et al.
Published: (2024)

Algorithmic Persuasion Through Simulation
by: Harris, Keegan, et al.
Published: (2023)

Practical Performative Policy Learning with Strategic Agents
by: Chen, Qianyi, et al.
Published: (2024)

Adaptive Bandit Algorithms for Contextual Matching Markets
by: Lin, Shiyun, et al.
Published: (2026)

Learning to Incentivize in Repeated Principal-Agent Problems with Adversarial Agent Arrivals
by: Liu, Junyan, et al.
Published: (2025)

Strategically Robust Multi-Agent Reinforcement Learning with Linear Function Approximation
by: Gonzales, Jake, et al.
Published: (2026)

Budget Pacing in Repeated Auctions: Regret and Efficiency without Convergence
by: Gaitonde, Jason, et al.
Published: (2022)

On Randomized Algorithms in Online Strategic Classification
by: Hutton, Chase, et al.
Published: (2026)

Incentivizing Desirable Effort Profiles in Strategic Classification: The Role of Causality and Uncertainty
by: Efthymiou, Valia, et al.
Published: (2025)

How to Strategize Human Content Creation in the Era of GenAI?
by: Esmaeili, Seyed A., et al.
Published: (2024)

Is Online Linear Optimization Sufficient for Strategic Robustness?
by: Cai, Yang, et al.
Published: (2026)

Geometry Meets Incentives: Sample-Efficient Incentivized Exploration with Linear Contexts
by: Schiffer, Benjamin, et al.
Published: (2025)

User Strategization and Trustworthy Algorithms
by: Cen, Sarah H., et al.
Published: (2023)

Creator Incentives in Recommender Systems: A Cooperative Game-Theoretic Approach for Stable and Fair Collaboration in Multi-Agent Bandits
by: Krishnamurthy, Ramakrishnan, et al.
Published: (2026)

Ad Auctions for LLMs via Retrieval Augmented Generation
by: Hajiaghayi, MohammadTaghi, et al.
Published: (2024)