Cover Image

Multiplayer Bandit Learning, from Competition to Cooperation

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Brânzei, Simina, Peres, Yuval
Format:	Preprint
Published:	2019
Subjects:	Computer Science and Game Theory Machine Learning Theoretical Economics
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Tit-for-Tat Dynamics and Market Volatility
by: Brânzei, Simina
Published: (2019)

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

Dueling Over Dessert, Mastering the Art of Repeated Cake Cutting
by: Brânzei, Simina, et al.
Published: (2024)

Emergent Alignment via Competition
by: Collina, Natalie, et al.
Published: (2025)

Deep Learning for Double Auction
by: Liu, Jiayin, et al.
Published: (2025)

Randomized Truthful Auctions with Learning Agents
by: Aggarwal, Gagan, et al.
Published: (2024)

Networked Information Aggregation via Machine Learning
by: Kearns, Michael, et al.
Published: (2025)

Learning to Coordinate Bidders in Non-Truthful Auctions
by: Fu, Hu, et al.
Published: (2025)

From No-Regret to Strategically Robust Learning in Repeated Auctions
by: Zhao, Junyao
Published: (2026)

Learning to Play Multi-Follower Bayesian Stackelberg Games
by: Personnat, Gerson, et al.
Published: (2025)

Persuading a Behavioral Agent: Approximately Best Responding and Learning
by: Chen, Yiling, et al.
Published: (2023)

The Bounds of Algorithmic Collusion; $Q$-learning, Gradient Learning, and the Folk Theorem
by: Askenazi-Golan, Galit, et al.
Published: (2024)

Federated Learning and Free-riding in a Competitive Market
by: Meng, Jiajun, et al.
Published: (2024)

Competitive and Revenue-Optimal Pricing with Budgets
by: Finster, Simon, et al.
Published: (2023)

Response Time Enhances Alignment with Heterogeneous Preferences
by: Echenique, Federico, et al.
Published: (2026)

A Linear Theory of Multi-Winner Voting
by: Xia, Lirong
Published: (2025)

Welfare, Improvability, and Variance: A Principal-Agent Approach to Optimal Benchmark Item Aggregation
by: Haupt, Andreas, et al.
Published: (2026)

How Humans Help LLMs: Assessing and Incentivizing Human Preference Annotators
by: Liu, Shang, et al.
Published: (2025)

Revisiting Fairness Impossibility with Endogenous Behavior
by: Penn, Elizabeth Maggie, et al.
Published: (2026)

Algorithmic Collusion Without Threats
by: Arunachaleswaran, Eshwar Ram, et al.
Published: (2024)

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

Swim till You Sink: Computing the Limit of a Game
by: Hakim, Rashida, et al.
Published: (2024)

Fair Allocation in Dynamic Mechanism Design
by: Fallah, Alireza, et al.
Published: (2024)

Online Assortment and Price Optimization Under Contextual Choice Models
by: Erginbas, Yigit Efe, et al.
Published: (2025)

Networked Information Aggregation for Binary Classification
by: Bateni, MohammadHossein, et al.
Published: (2026)

"Calibeating": Beating Forecasters at Their Own Game
by: Foster, Dean P., et al.
Published: (2022)

How to Sell High-Dimensional Data Optimally
by: Li, Andrew, et al.
Published: (2025)

Marketplace Operators Can Induce Competitive Pricing
by: Ding, Tiffany, et al.
Published: (2025)

Construction of Compromise Values for Cooperative Games
by: Gilles, Robert P., et al.
Published: (2025)

Competition Complexity in Multi-Item Auctions: Beyond VCG and Regularity
by: Beyhaghi, Hedyeh, et al.
Published: (2025)

A New Solution for Cooperative Game with Public Externalities
by: Fan, Juanjuan, et al.
Published: (2025)

Using "Failure Costs" to Guarantee Execution Quality in Competitive and Permissionless Order Flow Auctions
by: Watts, Alex, et al.
Published: (2025)

Opponent Modeling in Multiplayer Imperfect-Information Games
by: Ganzfried, Sam, et al.
Published: (2022)

A Geometric Nash Approach in Tuning the Learning Rate in Q-Learning Algorithm
by: Bonsu, Kwadwo Osei
Published: (2024)

Contracting with a Learning Agent
by: Guruganesh, Guru, et al.
Published: (2024)

Efficient Inverse Multiagent Learning
by: Goktas, Denizalp, et al.
Published: (2025)

Statistical Impossibility and Possibility of Aligning LLMs with Human Preferences: From Condorcet Paradox to Nash Equilibrium
by: Liu, Kaizhao, et al.
Published: (2025)

Generalized Principal-Agent Problem with a Learning Agent
by: Lin, Tao, et al.
Published: (2024)

Contractual Reinforcement Learning: Pulling Arms with Invisible Hands
by: Wu, Jibang, et al.
Published: (2024)

Paid with Models: Optimal Contract Design for Collaborative Machine Learning
by: Wang, Bingchen, et al.
Published: (2024)