Cover Image

Algorithmic Collusion Without Threats

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Arunachaleswaran, Eshwar Ram, Collina, Natalie, Kannan, Sampath, Roth, Aaron, Ziani, Juba
Format:	Preprint
Published:	2024
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

Breaking Algorithmic Collusion in Human-AI Ecosystems
by: Collina, Natalie, et al.
Published: (2025)

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

Clarification of `Algorithmic Collusion without Threats'
by: Hartline, Jason
Published: (2026)

Learning to Play Against Unknown Opponents
by: Arunachaleswaran, Eshwar Ram, et al.
Published: (2024)

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

Algorithmic Collusion is Algorithm Orchestration
by: Carissimo, Cesare, et al.
Published: (2025)

Regulation of Algorithmic Collusion
by: Hartline, Jason D., et al.
Published: (2024)

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

Pareto-Optimal Algorithms for Learning in Games
by: Arunachaleswaran, Eshwar Ram, et al.
Published: (2024)

Regulation of Algorithmic Collusion, Refined: Testing Pessimistic Calibrated Regret
by: Hartline, Jason D., et al.
Published: (2025)

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

On Mechanism Underlying Algorithmic Collusion
by: Xu, Zhang, et al.
Published: (2024)

Efficient Stackelberg Strategies for Finitely Repeated Games
by: Collina, Natalie, et al.
Published: (2022)

Collusion-Resilience in Transaction Fee Mechanism Design
by: Chung, Hao, et al.
Published: (2024)

Barriers to Collusion-resistant Transaction Fee Mechanisms
by: Gafni, Yotam, et al.
Published: (2024)

A Small Collusion is All You Need
by: Gafni, Yotam
Published: (2025)

Incentive-Compatible Collusion-Resistance via Posted Prices
by: Ferreira, Matheus V. X., et al.
Published: (2024)

Collusion-proof Auction Design using Side Information
by: Kudva, Sukanya, et al.
Published: (2025)

Learned Collusion
by: Compte, Olivier
Published: (2023)

Swap Regret and Correlated Equilibria Beyond Normal-Form Games
by: Arunachaleswaran, Eshwar Ram, et al.
Published: (2025)

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)

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

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

Multiplayer Bandit Learning, from Competition to Cooperation
by: Brânzei, Simina, et al.
Published: (2019)

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)

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

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

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

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

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

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

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)

"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)

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