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Game Theory

944 papers

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Papers

Learning in Markov Games with Adaptive Adversaries: Policy Regret, Fundamental Barriers, and Efficient Algorithms NIPS 2024
Local and Adaptive Mirror Descents in Extensive-Form Games NIPS 2024
No-Regret M${}^{\natural}$-Concave Function Maximization: Stochastic Bandit Algorithms and NP-Hardness of Adversarial Full-Information Setting NIPS 2024
No-Regret Learning for Fair Multi-Agent Social Welfare Optimization NIPS 2024
Reciprocal Reward Influence Encourages Cooperation From Self-Interested Agents NIPS 2024
Stochastic contextual bandits with graph feedback: from independence number to MAS number NIPS 2024
Truthful High Dimensional Sparse Linear Regression NIPS 2024
Solving Zero-Sum Markov Games with Continuous State via Spectral Dynamic Embedding NIPS 2024
Putting Gale & Shapley to Work: Guaranteeing Stability Through Learning NIPS 2024
FACT or Fiction: Can Truthful Mechanisms Eliminate Federated Free Riding? NIPS 2024
Secret Collusion among AI Agents: Multi-Agent Deception via Steganography NIPS 2024
Pricing and Competition for Generative AI NIPS 2024
Convergence of No-Swap-Regret Dynamics in Self-Play NIPS 2024
Online Bayesian Persuasion Without a Clue NIPS 2024
Contracting with a Learning Agent NIPS 2024
Bandits with Ranking Feedback NIPS 2024
Monoculture in Matching Markets NIPS 2024
Sample Complexity of Posted Pricing for a Single Item NIPS 2024
Fairness-Aware Meta-Learning via Nash Bargaining NIPS 2024
Multi-Winner Reconfiguration NIPS 2024
On the Optimality of Dilated Entropy and Lower Bounds for Online Learning in Extensive-Form Games NIPS 2024
Learning to Price Homogeneous Data NIPS 2024
Noisy Dual Mirror Descent: A Near Optimal Algorithm for Jointly-DP Convex Resource Allocation NIPS 2024
Improved Analysis for Bandit Learning in Matching Markets NIPS 2024
Learning Equilibria in Adversarial Team Markov Games: A Nonconvex-Hidden-Concave Min-Max Optimization Problem NIPS 2024