Multi-Objective Reinforcement Learning with Max-Min Criterion: A Game-Theoretic Approach
Fuente:
arXiv
Saved in:
| Main Authors: | Byeon, Woohyeon, Park, Giseung, Chae, Jongseong, Leshem, Amir, Sung, Youngchul |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Constrained Multi-Objective Reinforcement Learning with Max-Min Criterion
by: Park, Giseung, et al.
Published: (2026)
by: Park, Giseung, et al.
Published: (2026)
The Max-Min Formulation of Multi-Objective Reinforcement Learning: From Theory to a Model-Free Algorithm
by: Park, Giseung, et al.
Published: (2024)
by: Park, Giseung, et al.
Published: (2024)
Reward Dimension Reduction for Scalable Multi-Objective Reinforcement Learning
by: Park, Giseung, et al.
Published: (2025)
by: Park, Giseung, et al.
Published: (2025)
Flow Matching with Injected Noise for Offline-to-Online Reinforcement Learning
by: Shin, Yongjae, et al.
Published: (2026)
by: Shin, Yongjae, et al.
Published: (2026)
Flow Actor-Critic for Offline Reinforcement Learning
by: Chae, Jongseong, et al.
Published: (2026)
by: Chae, Jongseong, et al.
Published: (2026)
Adaptive Action Chunking via Multi-Chunk Q Value Estimation
by: Shin, Yongjae, et al.
Published: (2026)
by: Shin, Yongjae, et al.
Published: (2026)
Low-Rank Cyclostationarity Predictive Routing Is Almost as Good as Real-Time Data-based Routing
by: Oriel-Singer, et al.
Published: (2026)
by: Oriel-Singer, et al.
Published: (2026)
Near-Optimal Privacy-Preserving Learning for Max-Min Fair Multi-Agent Bandits
by: Leshem, Amir
Published: (2023)
by: Leshem, Amir
Published: (2023)
Bayesian Neural Networks: A Min-Max Game Framework
by: Hong, Junping, et al.
Published: (2023)
by: Hong, Junping, et al.
Published: (2023)
MinMaxMin $Q$-learning
by: Soffair, Nitsan, et al.
Published: (2024)
by: Soffair, Nitsan, et al.
Published: (2024)
Smooth Min-Max Monotonic Networks
by: Igel, Christian
Published: (2023)
by: Igel, Christian
Published: (2023)
Penalizing Infeasible Actions and Reward Scaling in Reinforcement Learning with Offline Data
by: Kim, Jeonghye, et al.
Published: (2025)
by: Kim, Jeonghye, et al.
Published: (2025)
A Meta-Learning Approach for Multi-Objective Reinforcement Learning in Sustainable Home Environments
by: Lu, Junlin, et al.
Published: (2024)
by: Lu, Junlin, et al.
Published: (2024)
Percentile Criterion Optimization in Offline Reinforcement Learning
by: Lobo, Elita A., et al.
Published: (2024)
by: Lobo, Elita A., et al.
Published: (2024)
Multi-Objective Reinforcement Learning for Water Management
by: Osika, Zuzanna, et al.
Published: (2025)
by: Osika, Zuzanna, et al.
Published: (2025)
Demonstration Guided Multi-Objective Reinforcement Learning
by: Lu, Junlin, et al.
Published: (2024)
by: Lu, Junlin, et al.
Published: (2024)
Bayesian Optimization for Function-Valued Responses under Min-Max Criteria
by: Ahadi, Pouya, et al.
Published: (2025)
by: Ahadi, Pouya, et al.
Published: (2025)
Game-Theoretic Robust Reinforcement Learning Handles Temporally-Coupled Perturbations
by: Liang, Yongyuan, et al.
Published: (2023)
by: Liang, Yongyuan, et al.
Published: (2023)
TREX: Trajectory Explanations for Multi-Objective Reinforcement Learning
by: Rajapakse, Dilina, et al.
Published: (2026)
by: Rajapakse, Dilina, et al.
Published: (2026)
Interpretability by Design for Efficient Multi-Objective Reinforcement Learning
by: Xia, Qiyue, et al.
Published: (2025)
by: Xia, Qiyue, et al.
Published: (2025)
iMTSP: Solving Min-Max Multiple Traveling Salesman Problem with Imperative Learning
by: Guo, Yifan, et al.
Published: (2024)
by: Guo, Yifan, et al.
Published: (2024)
Safe and Balanced: A Framework for Constrained Multi-Objective Reinforcement Learning
by: Gu, Shangding, et al.
Published: (2024)
by: Gu, Shangding, et al.
Published: (2024)
MinMax Recurrent Neural Cascades
by: Ronca, Alessandro
Published: (2026)
by: Ronca, Alessandro
Published: (2026)
An Offline Adaptation Framework for Constrained Multi-Objective Reinforcement Learning
by: Lin, Qian, et al.
Published: (2024)
by: Lin, Qian, et al.
Published: (2024)
In Search for Architectures and Loss Functions in Multi-Objective Reinforcement Learning
by: Terekhov, Mikhail, et al.
Published: (2024)
by: Terekhov, Mikhail, et al.
Published: (2024)
Polychromic Objectives for Reinforcement Learning
by: Hamid, Jubayer Ibn, et al.
Published: (2025)
by: Hamid, Jubayer Ibn, et al.
Published: (2025)
Navigating Trade-offs: Policy Summarization for Multi-Objective Reinforcement Learning
by: Osika, Zuzanna, et al.
Published: (2024)
by: Osika, Zuzanna, et al.
Published: (2024)
FairDICE: Fairness-Driven Offline Multi-Objective Reinforcement Learning
by: Kim, Woosung, et al.
Published: (2025)
by: Kim, Woosung, et al.
Published: (2025)
Scalable Multi-Objective and Meta Reinforcement Learning via Gradient Estimation
by: Zhang, Zhenshuo, et al.
Published: (2025)
by: Zhang, Zhenshuo, et al.
Published: (2025)
Combining Multi-Objective Bayesian Optimization with Reinforcement Learning for TinyML
by: Deutel, Mark, et al.
Published: (2023)
by: Deutel, Mark, et al.
Published: (2023)
STEMO: Early Spatio-temporal Forecasting with Multi-Objective Reinforcement Learning
by: Shao, Wei, et al.
Published: (2024)
by: Shao, Wei, et al.
Published: (2024)
MaxMin-RLHF: Alignment with Diverse Human Preferences
by: Chakraborty, Souradip, et al.
Published: (2024)
by: Chakraborty, Souradip, et al.
Published: (2024)
Optimistic Reinforcement Learning with Quantile Objectives
by: Alipour-Vaezi, Mohammad, et al.
Published: (2025)
by: Alipour-Vaezi, Mohammad, et al.
Published: (2025)
An Information-Theoretic Criterion for Efficient Data Synthesis
by: Li, Hanyu, et al.
Published: (2026)
by: Li, Hanyu, et al.
Published: (2026)
Deep Multi-Objective Reinforcement Learning for Utility-Based Infrastructural Maintenance Optimization
by: van Remmerden, Jesse, et al.
Published: (2024)
by: van Remmerden, Jesse, et al.
Published: (2024)
Hindsight Preference Replay Improves Preference-Conditioned Multi-Objective Reinforcement Learning
by: Shianifar, Jonaid, et al.
Published: (2026)
by: Shianifar, Jonaid, et al.
Published: (2026)
ADV-0: Closed-Loop Min-Max Adversarial Training for Long-Tail Robustness in Autonomous Driving
by: Nie, Tong, et al.
Published: (2026)
by: Nie, Tong, et al.
Published: (2026)
Multi-Objective Instruction-Aware Representation Learning in Procedural Content Generation RL
by: Kim, Sung-Hyun, et al.
Published: (2025)
by: Kim, Sung-Hyun, et al.
Published: (2025)
STAIRS-Former: Spatio-Temporal Attention with Interleaved Recursive Structure Transformer for Offline Multi-task Multi-agent Reinforcement Learning
by: Jeon, Jiwon, et al.
Published: (2026)
by: Jeon, Jiwon, et al.
Published: (2026)
Put CASH on Bandits: A Max K-Armed Problem for Automated Machine Learning
by: Balef, Amir Rezaei, et al.
Published: (2025)
by: Balef, Amir Rezaei, et al.
Published: (2025)
Similar Items
-
Constrained Multi-Objective Reinforcement Learning with Max-Min Criterion
by: Park, Giseung, et al.
Published: (2026) -
The Max-Min Formulation of Multi-Objective Reinforcement Learning: From Theory to a Model-Free Algorithm
by: Park, Giseung, et al.
Published: (2024) -
Reward Dimension Reduction for Scalable Multi-Objective Reinforcement Learning
by: Park, Giseung, et al.
Published: (2025) -
Flow Matching with Injected Noise for Offline-to-Online Reinforcement Learning
by: Shin, Yongjae, et al.
Published: (2026) -
Flow Actor-Critic for Offline Reinforcement Learning
by: Chae, Jongseong, et al.
Published: (2026)