"nash equilibrium" Papers
17 papers found
Conference
A Policy-Gradient Approach to Solving Imperfect-Information Games with Best-Iterate Convergence
Mingyang Liu, Gabriele Farina, Asuman Ozdaglar
ICLR 2025arXiv:2408.00751
3
citations
Classic but Everlasting: Traditional Gradient-Based Algorithms Converge Fast Even in Time-Varying Multi-Player Games
Yanzheng Chen, Jun Yu
ICLR 2025
Divergence-Regularized Discounted Aggregation: Equilibrium Finding in Multiplayer Partially Observable Stochastic Games
Runyu Lu, Yuanheng Zhu, Dongbin Zhao
ICLR 2025
3
citations
Efficient Last-Iterate Convergence in Solving Extensive-Form Games
Linjian Meng, Tianpei Yang, Youzhi Zhang et al.
NEURIPS 2025
Equilibrium Policy Generalization: A Reinforcement Learning Framework for Cross-Graph Zero-Shot Generalization in Pursuit-Evasion Games
Runyu Lu, Peng Zhang, Ruochuan Shi et al.
NEURIPS 2025arXiv:2511.00811
2
citations
On Feasible Rewards in Multi-Agent Inverse Reinforcement Learning
Till Freihaut, Giorgia Ramponi
NEURIPS 2025spotlightarXiv:2411.15046
2
citations
Principled Long-Tailed Generative Modeling via Diffusion Models
Pranoy Das, Kexin Fu, Abolfazl Hashemi et al.
NEURIPS 2025oral
Provable Robust Overfitting Mitigation in Wasserstein Distributionally Robust Optimization
Shuang Liu, Yihan Wang, Yifan Zhu et al.
ICLR 2025arXiv:2503.04315
Adaptively Perturbed Mirror Descent for Learning in Games
Kenshi Abe, Kaito Ariu, Mitsuki Sakamoto et al.
ICML 2024arXiv:2305.16610
9
citations
Causal Inference from Competing Treatments
Ana-Andreea Stoica, Vivian Y. Nastl, Moritz Hardt
ICML 2024arXiv:2406.03422
1
citations
Competition among Pairwise Lottery Contests
Xiaotie Deng, Hangxin Gan, Ningyuan Li et al.
AAAI 2024paperarXiv:2312.11953
4
citations
Human Alignment of Large Language Models through Online Preference Optimisation
Daniele Calandriello, Zhaohan Guo, REMI MUNOS et al.
ICML 2024arXiv:2403.08635
88
citations
Improving Sample Efficiency of Model-Free Algorithms for Zero-Sum Markov Games
Songtao Feng, Ming Yin, Yu-Xiang Wang et al.
ICML 2024arXiv:2308.08858
2
citations
Minimally Modifying a Markov Game to Achieve Any Nash Equilibrium and Value
Young Wu, Jeremy McMahan, Yiding Chen et al.
ICML 2024arXiv:2311.00582
3
citations
Model-Based RL for Mean-Field Games is not Statistically Harder than Single-Agent RL
Jiawei Huang, Niao He, Andreas Krause
ICML 2024arXiv:2402.05724
8
citations
Multi-Sender Persuasion: A Computational Perspective
Safwan Hossain, Tonghan Wang, Tao Lin et al.
ICML 2024arXiv:2402.04971
14
citations
Nash Learning from Human Feedback
REMI MUNOS, Michal Valko, Daniele Calandriello et al.
ICML 2024spotlightarXiv:2312.00886
195
citations