Cover Image

Model Selection for Average Reward RL with Application to Utility Maximization in Repeated Games

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Masoumian, Alireza, Wright, James R.
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Computer Science and Game Theory
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Provable Policy Gradient Methods for Average-Reward Markov Potential Games
by: Cheng, Min, et al.
Published: (2024)

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

Approximating Nash Equilibria in General-Sum Games via Meta-Learning
by: Sychrovský, David, et al.
Published: (2025)

Blind Inverse Game Theory: Jointly Decoding Rewards and Rationality in Entropy-Regularized Competitive Games
by: Virk, Hamza, et al.
Published: (2025)

Model-Based RL for Mean-Field Games is not Statistically Harder than Single-Agent RL
by: Huang, Jiawei, et al.
Published: (2024)

RL-CFR: Improving Action Abstraction for Imperfect Information Extensive-Form Games with Reinforcement Learning
by: Li, Boning, et al.
Published: (2024)

From Average-Iterate to Last-Iterate Convergence in Games: A Reduction and Its Applications
by: Cai, Yang, et al.
Published: (2025)

How to Evaluate Behavioral Models
by: d'Eon, Greg, et al.
Published: (2023)

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

ElementaryNet: A Non-Strategic Neural Network for Predicting Human Behavior in Normal-Form Games
by: d'Eon, Greg, et al.
Published: (2025)

Safe Pareto Improvements for Expected Utility Maximizers in Program Games
by: DiGiovanni, Anthony, et al.
Published: (2024)

A Tight Regret Analysis of Non-Parametric Repeated Contextual Brokerage
by: Bachoc, François, et al.
Published: (2025)

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

Barriers to Welfare Maximization with No-Regret Learning
by: Anagnostides, Ioannis, et al.
Published: (2024)

DUPRE: Data Utility Prediction for Efficient Data Valuation
by: Pham, Kieu Thao Nguyen, et al.
Published: (2025)

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

A Learning Algorithm That Attains the Human Optimum in a Repeated Human-Machine Interaction Game
by: Isa, Jason T., et al.
Published: (2025)

The Representation-Rationalizability Tradeoff in Reward Learning
by: Dong, Jing, et al.
Published: (2026)

Market Games for Generative Models: Equilibria, Welfare, and Strategic Entry
by: Wei, Xiukun, et al.
Published: (2026)

From Stream to Pool: Pricing Under the Law of Diminishing Marginal Utility
by: Cui, Titing, et al.
Published: (2023)

Shapley-Guided Utility Learning for Effective Graph Inference Data Valuation
by: Chi, Hongliang, et al.
Published: (2025)

Enhancing Affine Maximizer Auctions with Correlation-Aware Payment
by: Sun, Haoran, et al.
Published: (2026)

Robust Adversarial Reinforcement Learning in Stochastic Games via Sequence Modeling
by: Tang, Xiaohang, et al.
Published: (2025)

Nearly Tight Regret Bounds for Profit Maximization in Bilateral Trade
by: Di Gregorio, Simone, et al.
Published: (2025)

Profit Maximization in Bilateral Trade against a Smooth Adversary
by: Di Gregorio, Simone, et al.
Published: (2026)

On the Decomposition of Differential Game
by: Zhou, Nanxiang, et al.
Published: (2024)

Autobidding Arena: unified evaluation of the classical and RL-based autobidding algorithms
by: Pudovikov, Andrey, et al.
Published: (2025)

Double Oracle Neural Architecture Search for Game Theoretic Deep Learning Models
by: Aung, Aye Phyu Phyu, et al.
Published: (2024)

Heterogeneous Data Game: Characterizing the Model Competition Across Multiple Data Sources
by: Xu, Renzhe, et al.
Published: (2025)

Learning to Bid in Non-Stationary Repeated First-Price Auctions
by: Hu, Zihao, et al.
Published: (2025)

No Coin Left Behind: Maximizing Strategic Surplus Against No-Regret Dynamics
by: Su, Yiheng, et al.
Published: (2026)

Distributionally Robust Markov Games with Average Reward
by: Roch, Zachary, et al.
Published: (2025)

Corrupted Learning Dynamics in Games
by: Tsuchiya, Taira, et al.
Published: (2024)

Learning in Structured Stackelberg Games
by: Balcan, Maria-Florina, et al.
Published: (2025)

Learning to Steer Learners in Games
by: Zhang, Yizhou, et al.
Published: (2025)

Regret Minimization for Piecewise Linear Rewards: Contracts, Auctions, and Beyond
by: Bacchiocchi, Francesco, et al.
Published: (2025)

Understanding Model Selection For Learning In Strategic Environments
by: Handina, Tinashe, et al.
Published: (2024)

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

Neural Mean-Field Games: Extending Mean-Field Game Theory with Neural Stochastic Differential Equations
by: Thöni, Anna C. M., et al.
Published: (2025)

Regulation Games for Trustworthy Machine Learning
by: Yaghini, Mohammad, et al.
Published: (2024)