Operator-Guided Invariance Learning for Continuous Reinforcement Learning
Fuente:
arXiv
Saved in:
| Main Authors: | Zhang, Zuyuan, Yu, Fei Xu, Lan, Tian |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Matrix-Space Reinforcement Learning for Reusing Local Transition Geometry
by: Zhang, Zuyuan, et al.
Published: (2026)
by: Zhang, Zuyuan, et al.
Published: (2026)
Manifold-Constrained Energy-Based Transition Models for Offline Reinforcement Learning
by: Fang, Zeyu, et al.
Published: (2026)
by: Fang, Zeyu, et al.
Published: (2026)
Cochain Perspectives on Temporal-Difference Signals for Learning Beyond Markov Dynamics
by: Zhang, Zuyuan, et al.
Published: (2026)
by: Zhang, Zuyuan, et al.
Published: (2026)
Metric-Gradient Projection for Stable Multi-Agent Policy Learning
by: Zhang, Zuyuan, et al.
Published: (2026)
by: Zhang, Zuyuan, et al.
Published: (2026)
Geometry of Drifting MDPs with Path-Integral Stability Certificates
by: Zhang, Zuyuan, et al.
Published: (2026)
by: Zhang, Zuyuan, et al.
Published: (2026)
Tail-Risk-Safe Monte Carlo Tree Search under PAC-Level Guarantees
by: Zhang, Zuyuan, et al.
Published: (2025)
by: Zhang, Zuyuan, et al.
Published: (2025)
Interactive Critique-Revision Training for Reliable Structured LLM Generation
by: Yu, Fei Xu, et al.
Published: (2026)
by: Yu, Fei Xu, et al.
Published: (2026)
Continuous Invariance Learning
by: Lin, Yong, et al.
Published: (2023)
by: Lin, Yong, et al.
Published: (2023)
Cooperative Backdoor Attack in Decentralized Reinforcement Learning with Theoretical Guarantee
by: Gao, Mengtong, et al.
Published: (2024)
by: Gao, Mengtong, et al.
Published: (2024)
Weight Clipping for Deep Continual and Reinforcement Learning
by: Elsayed, Mohamed, et al.
Published: (2024)
by: Elsayed, Mohamed, et al.
Published: (2024)
AFCL: Analytic Federated Continual Learning for Spatio-Temporal Invariance of Non-IID Data
by: Tang, Jianheng, et al.
Published: (2025)
by: Tang, Jianheng, et al.
Published: (2025)
Normality-Guided Distributional Reinforcement Learning for Continuous Control
by: Byun, Ju-Seung, et al.
Published: (2022)
by: Byun, Ju-Seung, et al.
Published: (2022)
Learning to Optimize for Reinforcement Learning
by: Lan, Qingfeng, et al.
Published: (2023)
by: Lan, Qingfeng, et al.
Published: (2023)
Adaptive Advantage-Guided Policy Regularization for Offline Reinforcement Learning
by: Liu, Tenglong, et al.
Published: (2024)
by: Liu, Tenglong, et al.
Published: (2024)
Reinforcement Learning-Guided Semi-Supervised Learning
by: Heidari, Marzi, et al.
Published: (2024)
by: Heidari, Marzi, et al.
Published: (2024)
Test-driven Reinforcement Learning in Continuous Control
by: Yu, Zhao, et al.
Published: (2025)
by: Yu, Zhao, et al.
Published: (2025)
Interpretable Operator Learning for Inverse Problems via Adaptive Spectral Filtering: Convergence and Discretization Invariance
by: Dong, Hang-Cheng, et al.
Published: (2026)
by: Dong, Hang-Cheng, et al.
Published: (2026)
Learning Action-based Representations Using Invariance
by: Rudolph, Max, et al.
Published: (2024)
by: Rudolph, Max, et al.
Published: (2024)
A Comparative Evaluation of Teacher-Guided Reinforcement Learning Techniques for Autonomous Cyber Operations
by: Tholl, Konur, et al.
Published: (2025)
by: Tholl, Konur, et al.
Published: (2025)
A priori Estimates for Deep Residual Network in Continuous-time Reinforcement Learning
by: Yin, Shuyu, et al.
Published: (2024)
by: Yin, Shuyu, et al.
Published: (2024)
Learning with Exact Invariances in Polynomial Time
by: Soleymani, Ashkan, et al.
Published: (2025)
by: Soleymani, Ashkan, et al.
Published: (2025)
Opinion-Guided Reinforcement Learning
by: Dagenais, Kyanna, et al.
Published: (2024)
by: Dagenais, Kyanna, et al.
Published: (2024)
MICRO: Model-Based Offline Reinforcement Learning with a Conservative Bellman Operator
by: Liu, Xiao-Yin, et al.
Published: (2023)
by: Liu, Xiao-Yin, et al.
Published: (2023)
Counterfactual Explanations for Continuous Action Reinforcement Learning
by: Dong, Shuyang, et al.
Published: (2025)
by: Dong, Shuyang, et al.
Published: (2025)
Continual Learning as Computationally Constrained Reinforcement Learning
by: Kumar, Saurabh, et al.
Published: (2023)
by: Kumar, Saurabh, et al.
Published: (2023)
Reinforcement Learning With Sparse-Executing Actions via Sparsity Regularization
by: Pang, Jing-Cheng, et al.
Published: (2021)
by: Pang, Jing-Cheng, et al.
Published: (2021)
Can LLMs Guide Their Own Exploration? Gradient-Guided Reinforcement Learning for LLM Reasoning
by: Liang, Zhenwen, et al.
Published: (2025)
by: Liang, Zhenwen, et al.
Published: (2025)
Reflex: Reinforcement Learning with Reflection Symmetry Exploitation in State-Based Continuous Control
by: Zhen, Shuai, et al.
Published: (2026)
by: Zhen, Shuai, et al.
Published: (2026)
ORPR: An OR-Guided Pretrain-then-Reinforce Learning Model for Inventory Management
by: Zhao, Lingjie, et al.
Published: (2025)
by: Zhao, Lingjie, et al.
Published: (2025)
Reinforcement Learning by Guided Safe Exploration
by: Yang, Qisong, et al.
Published: (2023)
by: Yang, Qisong, et al.
Published: (2023)
A Contractive Feedback Semantics for Reinforcement Learning
by: Zhang, Zuyuan
Published: (2026)
by: Zhang, Zuyuan
Published: (2026)
Rethinking the Foundations for Continual Reinforcement Learning
by: Elelimy, Esraa, et al.
Published: (2025)
by: Elelimy, Esraa, et al.
Published: (2025)
A Survey of Continual Reinforcement Learning
by: Pan, Chaofan, et al.
Published: (2025)
by: Pan, Chaofan, et al.
Published: (2025)
Parseval Regularization for Continual Reinforcement Learning
by: Chung, Wesley, et al.
Published: (2024)
by: Chung, Wesley, et al.
Published: (2024)
DESIRE: Dynamic Knowledge Consolidation for Rehearsal-Free Continual Learning
by: Guo, Haiyang, et al.
Published: (2024)
by: Guo, Haiyang, et al.
Published: (2024)
Reason in Chains, Learn in Trees: Self-Rectification and Grafting for Multi-turn Agent Policy Optimization
by: Li, Yu, et al.
Published: (2026)
by: Li, Yu, et al.
Published: (2026)
Enabling High Data Throughput Reinforcement Learning on GPUs: A Domain Agnostic Framework for Data-Driven Scientific Research
by: Lan, Tian, et al.
Published: (2024)
by: Lan, Tian, et al.
Published: (2024)
Subgoal Graph-Augmented Planning for LLM-Guided Open-World Reinforcement Learning
by: Fan, Shanwei, et al.
Published: (2025)
by: Fan, Shanwei, et al.
Published: (2025)
One-Shot Imitation Learning with Invariance Matching for Robotic Manipulation
by: Zhang, Xinyu, et al.
Published: (2024)
by: Zhang, Xinyu, et al.
Published: (2024)
Deep Reinforcement Learning Guided Improvement Heuristic for Job Shop Scheduling
by: Zhang, Cong, et al.
Published: (2022)
by: Zhang, Cong, et al.
Published: (2022)
Similar Items
-
Matrix-Space Reinforcement Learning for Reusing Local Transition Geometry
by: Zhang, Zuyuan, et al.
Published: (2026) -
Manifold-Constrained Energy-Based Transition Models for Offline Reinforcement Learning
by: Fang, Zeyu, et al.
Published: (2026) -
Cochain Perspectives on Temporal-Difference Signals for Learning Beyond Markov Dynamics
by: Zhang, Zuyuan, et al.
Published: (2026) -
Metric-Gradient Projection for Stable Multi-Agent Policy Learning
by: Zhang, Zuyuan, et al.
Published: (2026) -
Geometry of Drifting MDPs with Path-Integral Stability Certificates
by: Zhang, Zuyuan, et al.
Published: (2026)