Cover Image

Learning in Online Principal-Agent Interactions: The Power of Menus

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Han, Minbiao, Albert, Michael, Xu, Haifeng
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

Is Learning Effective in Dynamic Strategic Interactions? Evidence from Stackelberg Games
by: Albert, Michael, et al.
Published: (2025)

Optimal Pricing for Data-Augmented AutoML Marketplaces
by: Han, Minbiao, et al.
Published: (2023)

Generalized Principal-Agency: Contracts, Information, Games and Beyond
by: Gan, Jiarui, et al.
Published: (2022)

Data Auctions for Retrieval Augmented Generation
by: Han, Minbiao, et al.
Published: (2025)

New Guarantees for Learning Revenue Maximizing Menus of Lotteries and Two-Part Tariffs
by: Balcan, Maria-Florina, et al.
Published: (2023)

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

Escape Sensing Games: Detection-vs-Evasion in Security Applications
by: Boehmer, Niclas, et al.
Published: (2024)

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

Principal-Agent Reinforcement Learning: Orchestrating AI Agents with Contracts
by: Ivanov, Dima, et al.
Published: (2024)

Stochastic Principal-Agent Problems: Efficient Computation and Learning
by: Gan, Jiarui, et al.
Published: (2023)

Robust Stackelberg Equilibria
by: Gan, Jiarui, et al.
Published: (2023)

Is Knowledge Power? On the (Im)possibility of Learning from Strategic Interactions
by: Ananthakrishnan, Nivasini, et al.
Published: (2024)

Information Design in the Principal-Agent Problem
by: Babichenko, Yakov, et al.
Published: (2022)

Principal-Agent Hypothesis Testing
by: Bates, Stephen, et al.
Published: (2022)

Learning Local Stackelberg Equilibria from Repeated Interactions with a Learning Agent
by: Ananthakrishnan, Nivasini, et al.
Published: (2025)

Intelligent Agents for Auction-based Federated Learning: A Survey
by: Tang, Xiaoli, et al.
Published: (2024)

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

T-TAMER: Provably Taming Trade-offs in ML Serving
by: Yang, Yuanyuan, et al.
Published: (2025)

Strategic Filtering for Content Moderation: Free Speech or Free of Distortion?
by: Ahmadi, Saba, et al.
Published: (2025)

Fair Contracts in Principal-Agent Games with Heterogeneous Types
by: Tłuczek, Jakub, et al.
Published: (2025)

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

Online Learning with Bounded Recall
by: Schneider, Jon, et al.
Published: (2022)

PPA-Game: Characterizing and Learning Competitive Dynamics Among Online Content Creators
by: Xu, Renzhe, et al.
Published: (2024)

Taming Equilibrium Bias in Risk-Sensitive Multi-Agent Reinforcement Learning
by: Fei, Yingjie, et al.
Published: (2024)

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

Should Decision-Makers Reveal Classifiers in Online Strategic Classification?
by: Shao, Han, et al.
Published: (2025)

An Instrumental Value for Data Production and its Application to Data Pricing
by: Ai, Rui, et al.
Published: (2024)

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

Online Auction Design Using Distribution-Free Uncertainty Quantification with Applications to E-Commerce
by: Han, Jiale, et al.
Published: (2024)

Learning-Augmented Online Bidding in Stochastic Settings
by: Angelopoulos, Spyros, et al.
Published: (2025)

The Relationship between No-Regret Learning and Online Conformal Prediction
by: Ramalingam, Ramya, et al.
Published: (2025)

Online Learning for Equilibrium Pricing in Markets under Incomplete Information
by: Jalota, Devansh, et al.
Published: (2023)

Honor Among Bandits: No-Regret Learning for Online Fair Division
by: Procaccia, Ariel D., et al.
Published: (2024)

A New Benchmark for Online Learning with Budget-Balancing Constraints
by: Braverman, Mark, et al.
Published: (2025)

Improved Regret Bounds for Online Fair Division with Bandit Learning
by: Schiffer, Benjamin, et al.
Published: (2025)

Online Learning under Budget and ROI Constraints via Weak Adaptivity
by: Castiglioni, Matteo, et al.
Published: (2023)

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

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

On the Optimality of Dilated Entropy and Lower Bounds for Online Learning in Extensive-Form Games
by: Fan, Zhiyuan, et al.
Published: (2024)

Factorised Active Inference for Strategic Multi-Agent Interactions
by: Ruiz-Serra, Jaime, et al.
Published: (2024)