No-Regret Learning for Fair Multi-Agent Social Welfare Optimization
Fuente:
arXiv
Saved in:
| Main Authors: | Zhang, Mengxiao, Vuong, Ramiro Deo-Campo, Luo, Haipeng |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Welfare and Fairness in Multi-objective Reinforcement Learning
by: Fan, Zimeng, et al.
Published: (2022)
by: Fan, Zimeng, et al.
Published: (2022)
Easy as ABCs: Unifying Boltzmann Q-Learning and Counterfactual Regret Minimization
by: D'Amico-Wong, Luca, et al.
Published: (2024)
by: D'Amico-Wong, Luca, et al.
Published: (2024)
Partially Observable Multi-Agent Reinforcement Learning with Information Sharing
by: Liu, Xiangyu, et al.
Published: (2023)
by: Liu, Xiangyu, et al.
Published: (2023)
Fair Contracts in Principal-Agent Games with Heterogeneous Types
by: Tłuczek, Jakub, et al.
Published: (2025)
by: Tłuczek, Jakub, et al.
Published: (2025)
AdaFair-MARL: Enforcing Adaptive Fairness Constraints in Multi-Agent Reinforcement Learning
by: Ekpo, Promise, et al.
Published: (2025)
by: Ekpo, Promise, et al.
Published: (2025)
Procedural Fairness in Multi-Agent Bandits
by: Caiata, Joshua, et al.
Published: (2026)
by: Caiata, Joshua, et al.
Published: (2026)
Breaking the Curse of Multiagency in Robust Multi-Agent Reinforcement Learning
by: Shi, Laixi, et al.
Published: (2024)
by: Shi, Laixi, et al.
Published: (2024)
Matching Multiple Experts: On the Exploitability of Multi-Agent Imitation Learning
by: Bergerault, Antoine, et al.
Published: (2026)
by: Bergerault, Antoine, et al.
Published: (2026)
Multi-Agent Reinforcement Learning in Cybersecurity: From Fundamentals to Applications
by: Landolt, Christoph R., et al.
Published: (2025)
by: Landolt, Christoph R., et al.
Published: (2025)
Strategically Robust Multi-Agent Reinforcement Learning with Linear Function Approximation
by: Gonzales, Jake, et al.
Published: (2026)
by: Gonzales, Jake, et al.
Published: (2026)
Principal-Agent Reinforcement Learning: Orchestrating AI Agents with Contracts
by: Ivanov, Dima, et al.
Published: (2024)
by: Ivanov, Dima, et al.
Published: (2024)
Factorised Active Inference for Strategic Multi-Agent Interactions
by: Ruiz-Serra, Jaime, et al.
Published: (2024)
by: Ruiz-Serra, Jaime, et al.
Published: (2024)
Competitive Algorithms for Multi-Agent Ski-Rental Problems
by: Wang, Xuchuang, et al.
Published: (2025)
by: Wang, Xuchuang, et al.
Published: (2025)
Stochastic Principal-Agent Problems: Efficient Computation and Learning
by: Gan, Jiarui, et al.
Published: (2023)
by: Gan, Jiarui, et al.
Published: (2023)
Optimizing Social Utility in Sequential Experiments
by: Velasco, Ander Artola, et al.
Published: (2026)
by: Velasco, Ander Artola, et al.
Published: (2026)
On the Complexity of Learning to Cooperate with Populations of Socially Rational Agents
by: Loftin, Robert, et al.
Published: (2024)
by: Loftin, Robert, et al.
Published: (2024)
Learning Bilateral Team Formation in Cooperative Multi-Agent Reinforcement Learning
by: Moslemi, Koorosh, et al.
Published: (2025)
by: Moslemi, Koorosh, et al.
Published: (2025)
Preference-Based Multi-Agent Reinforcement Learning: Data Coverage and Algorithmic Techniques
by: Zhang, Natalia, et al.
Published: (2024)
by: Zhang, Natalia, et al.
Published: (2024)
Socially-Weighted Alignment: A Game-Theoretic Framework for Multi-Agent LLM Systems
by: Mumcu, Furkan, et al.
Published: (2026)
by: Mumcu, Furkan, et al.
Published: (2026)
Shapley Machine: A Game-Theoretic Framework for N-Agent Ad Hoc Teamwork
by: Wang, Jianhong, et al.
Published: (2025)
by: Wang, Jianhong, et al.
Published: (2025)
Survey on Strategic Mining in Blockchain: A Reinforcement Learning Approach
by: Li, Jichen, et al.
Published: (2025)
by: Li, Jichen, et al.
Published: (2025)
Exploring Welfare Maximization and Fairness in Participatory Budgeting
by: Sreedurga, Gogulapati
Published: (2024)
by: Sreedurga, Gogulapati
Published: (2024)
GTAlign: Game-Theoretic Alignment of LLM Assistants for Social Welfare
by: Zhu, Siqi, et al.
Published: (2025)
by: Zhu, Siqi, et al.
Published: (2025)
Incentivize Contribution and Learn Parameters Too: Federated Learning with Strategic Data Owners
by: Doshi, Drashthi, et al.
Published: (2025)
by: Doshi, Drashthi, et al.
Published: (2025)
Independent Learning in Constrained Markov Potential Games
by: Jordan, Philip, et al.
Published: (2024)
by: Jordan, Philip, et al.
Published: (2024)
Policy Optimization and Multi-agent Reinforcement Learning for Mean-variance Team Stochastic Games
by: Hu, Junkai, et al.
Published: (2025)
by: Hu, Junkai, et al.
Published: (2025)
Unsynchronized Decentralized Q-Learning: Two Timescale Analysis By Persistence
by: Yongacoglu, Bora, et al.
Published: (2023)
by: Yongacoglu, Bora, et al.
Published: (2023)
Efficient and Scalable Deep Reinforcement Learning for Mean Field Control Games
by: Peng, Nianli, et al.
Published: (2024)
by: Peng, Nianli, et al.
Published: (2024)
Energy Minimization for Participatory Federated Learning in IoT Analyzed via Game Theory
by: Buratto, Alessandro, et al.
Published: (2025)
by: Buratto, Alessandro, et al.
Published: (2025)
Heterogeneous Multi-Agent Bandits with Parsimonious Hints
by: Mirfakhar, Amirmahdi, et al.
Published: (2025)
by: Mirfakhar, Amirmahdi, et al.
Published: (2025)
Independent Learning of Nash Equilibria in Partially Observable Markov Potential Games with Decoupled Dynamics
by: Jordan, Philip, et al.
Published: (2026)
by: Jordan, Philip, et al.
Published: (2026)
Convex Markov Games and Beyond: New Proof of Existence, Characterization and Learning Algorithms for Nash Equilibria
by: Barakat, Anas, et al.
Published: (2026)
by: Barakat, Anas, et al.
Published: (2026)
How Market Volatility Shapes Algorithmic Collusion: A Comparative Analysis of Learning-Based Pricing Algorithms
by: Sravon, Aheer, et al.
Published: (2025)
by: Sravon, Aheer, et al.
Published: (2025)
A Single Online Agent Can Efficiently Learn Mean Field Games
by: Zhang, Chenyu, et al.
Published: (2024)
by: Zhang, Chenyu, et al.
Published: (2024)
Provably Convergent Actor-Critic for MARL through Risk-aversion
by: Zhang, Yizhou, et al.
Published: (2026)
by: Zhang, Yizhou, et al.
Published: (2026)
RuleSmith: Multi-Agent LLMs for Automated Game Balancing
by: Zeng, Ziyao, et al.
Published: (2026)
by: Zeng, Ziyao, et al.
Published: (2026)
Experience-replay Innovative Dynamics
by: Zhang, Tuo, et al.
Published: (2025)
by: Zhang, Tuo, et al.
Published: (2025)
Emergent Dominance Hierarchies in Reinforcement Learning Agents
by: Rachum, Ram, et al.
Published: (2024)
by: Rachum, Ram, et al.
Published: (2024)
Altruism and Fair Objective in Mixed-Motive Markov games
by: Xu, Yao-hua Franck, et al.
Published: (2026)
by: Xu, Yao-hua Franck, et al.
Published: (2026)
Agent-Temporal Credit Assignment for Optimal Policy Preservation in Sparse Multi-Agent Reinforcement Learning
by: Kapoor, Aditya, et al.
Published: (2024)
by: Kapoor, Aditya, et al.
Published: (2024)
Similar Items
-
Welfare and Fairness in Multi-objective Reinforcement Learning
by: Fan, Zimeng, et al.
Published: (2022) -
Easy as ABCs: Unifying Boltzmann Q-Learning and Counterfactual Regret Minimization
by: D'Amico-Wong, Luca, et al.
Published: (2024) -
Partially Observable Multi-Agent Reinforcement Learning with Information Sharing
by: Liu, Xiangyu, et al.
Published: (2023) -
Fair Contracts in Principal-Agent Games with Heterogeneous Types
by: Tłuczek, Jakub, et al.
Published: (2025) -
AdaFair-MARL: Enforcing Adaptive Fairness Constraints in Multi-Agent Reinforcement Learning
by: Ekpo, Promise, et al.
Published: (2025)