Image de couverture de livre

Roping in Uncertainty: Robustness and Regularization in Markov Games

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	McMahan, Jeremy, Artiglio, Giovanni, Xie, Qiaomin
Format:	Preprint
Publié:	2024
Sujets:	Computer Science and Game Theory Data Structures and Algorithms Machine Learning
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Anytime-Constrained Equilibria in Polynomial Time
par: McMahan, Jeremy
Publié: (2024)

Inception: Efficiently Computable Misinformation Attacks on Markov Games
par: McMahan, Jeremy, et autres
Publié: (2024)

Data Poisoning to Fake a Nash Equilibrium in Markov Games
par: Wu, Young, et autres
Publié: (2023)

Learning in Stackelberg Games with Non-myopic Agents
par: Haghtalab, Nika, et autres
Publié: (2022)

Deterministic Policies for Constrained Reinforcement Learning in Polynomial Time
par: McMahan, Jeremy
Publié: (2024)

Single-Sample and Robust Online Resource Allocation
par: Ghuge, Rohan, et autres
Publié: (2025)

Computing Optimal Regularizers for Online Linear Optimization
par: Gatmiry, Khashayar, et autres
Publié: (2024)

Polynomial-Time Approximability of Constrained Reinforcement Learning
par: McMahan, Jeremy
Publié: (2025)

Envy-freeness in 3D Hedonic Games
par: McKay, Michael, et autres
Publié: (2022)

Optimal Attack and Defense for Reinforcement Learning
par: McMahan, Jeremy, et autres
Publié: (2023)

Optimally Installing Strict Equilibria
par: McMahan, Jeremy, et autres
Publié: (2025)

Repeated Contracting with Multiple Non-Myopic Agents: Policy Regret and Limited Liability
par: Collina, Natalie, et autres
Publié: (2024)

Strategizing against No-Regret Learners in First-Price Auctions
par: Rubinstein, Aviad, et autres
Publié: (2024)

Learning Safe Strategies for Value Maximizing Buyers in Uniform Price Auctions
par: Golrezaei, Negin, et autres
Publié: (2024)

Procurement Auctions via Approximately Optimal Submodular Optimization
par: Deng, Yuan, et autres
Publié: (2024)

Improved Algorithms for Contextual Dynamic Pricing
par: Tullii, Matilde, et autres
Publié: (2024)

Tractable Agreement Protocols
par: Collina, Natalie, et autres
Publié: (2024)

Online Combinatorial Allocations and Auctions with Few Samples
par: Dütting, Paul, et autres
Publié: (2024)

High dimensional online calibration in polynomial time
par: Peng, Binghui
Publié: (2025)

Repeated Bilateral Trade Against a Smoothed Adversary
par: Cesa-Bianchi, Nicolò, et autres
Publié: (2023)

Improved Regret and Contextual Linear Extension for Pandora's Box and Prophet Inequality
par: Liu, Junyan, et autres
Publié: (2025)

Online Bidding Algorithms with Strict Return on Spend (ROS) Constraint
par: Vaze, Rahul, et autres
Publié: (2025)

High-Dimensional Calibration from Swap Regret
par: Fishelson, Maxwell, et autres
Publié: (2025)

On the Learning Curves of Revenue Maximization
par: Hanneke, Steve, et autres
Publié: (2026)

An $α$-regret analysis of Adversarial Bilateral Trade
par: Azar, Yossi, et autres
Publié: (2022)

Fixed Point Computation: Beating Brute Force with Smoothed Analysis
par: Attias, Idan, et autres
Publié: (2025)

Bandit Sequential Posted Pricing via Half-Concavity
par: Singla, Sahil, et autres
Publié: (2023)

The Role of Transparency in Repeated First-Price Auctions with Unknown Valuations
par: Cesa-Bianchi, Nicolò, et autres
Publié: (2023)

Simultaneous Swap Regret Minimization via KL-Calibration
par: Luo, Haipeng, et autres
Publié: (2025)

Collaborative Prediction: Tractable Information Aggregation via Agreement
par: Collina, Natalie, et autres
Publié: (2025)

Contextual Learning for Stochastic Optimization
par: Heuser, Anna, et autres
Publié: (2025)

Bandit Social Learning: Exploration under Myopic Behavior
par: Banihashem, Kiarash, et autres
Publié: (2023)

Smooth Nash Equilibria: Algorithms and Complexity
par: Daskalakis, Constantinos, et autres
Publié: (2023)

Water-Filling is Universally Minimax Optimal
par: Banerjee, Siddhartha, et autres
Publié: (2026)

Incentivizing Exploration with Selective Data Disclosure
par: Immorlica, Nicole, et autres
Publié: (2018)

Learning Optimal Posted Prices for a Unit-Demand Buyer
par: Teng, Yifeng, et autres
Publié: (2025)

Adaptive Discretization against an Adversary: Lipschitz bandits, Dynamic Pricing, and Auction Tuning
par: Podimata, Chara, et autres
Publié: (2020)

Efficiently Solving Turn-Taking Stochastic Games with Extensive-Form Correlation
par: Zhang, Hanrui, et autres
Publié: (2024)

Stable Matching with Predictions: Robustness and Efficiency under Pruned Preferences
par: McCauley, Samuel, et autres
Publié: (2026)

Lipschitz Continuous Allocations for Optimization Games
par: Kumabe, Soh, et autres
Publié: (2024)